Abstract
Background/Aim: Ovarian carcinoma is a difficult-to-treat cancer. It is often resistant to chemotherapy and targeted therapy. The 5-year survival rates of patients with advanced tumors are usually below 40%. Immunotherapy represents an emerging treatment option. We investigated the prognostic significance of the oncogenic transcription factor AP-1, formed by the dimerization of FOS and JUN family members.
Patients and Methods: Using the KM Plotter algorithm, Kaplan-Meier statistics were applied to calculate survival times of 373 patients with ovarian carcinoma from The Cancer Genome Atlas (TCGA). Expression of AP-1 dimer components (FOS, FOSB, FOSL1, FOSL2, JUN, JUNB, and JUND) was based on RNA sequencing. To estimate immune response, increased or decreased tumor infiltration of immune cells was assessed.
Results: High expression of JUNB alone or in combination with FOSB, FOSL1, or FOSL2 (but not with JUN, JUND, or FOS) significantly correlated with shorter survival. Hierarchical clustering of the survival analyses revealed that JUNB (alone or together with FOSB, FOSL1, or FOSL2), combined with decreased counts of CD8+ cytotoxic T cells, regulatory T cells, or natural killer cells, correlated with shorter survival. Conversely, increased tumor infiltration with type 2 T helper cells or basophilic granulocytes and JUNB-containing AP-1 dimers also correlated with poor overall survival.
Conclusion: Specific combinations of AP-1 dimer components were of prognostic value for shorter overall survival and were associated with immune cell infiltration linked to “cold” phenotypes non-responsive to immunotherapy. JUNB-containing AP-1 dimers may promote immune evasion and tumor-progressing immune responses. Our results may help identify high-risk patients and support the evaluation of JUNB-containing AP-1 dimers as prognostic factors for ovarian carcinoma.
Introduction
Ovarian cancer is one of the most common and deadly types of cancer in gynecology (1). Due to its asymptomatic onset, it is often only diagnosed at an advanced stage. Ovarian cancer is the seventh most common cancer in women worldwide, and the fifth leading cause of cancer death. There are approximately 300,000 new cases worldwide each year, and more than 200,000 deaths from this disease. The majority of diagnoses occur in women between the ages of 55 and 75. Ovarian cancer is often discovered in postmenopausal women, but there are also cases in younger women, especially those with genetic predispositions (e.g., BRCA1/2 mutations). Women with a family history of ovarian cancer or certain genetic mutations, such as BRCA1/2, are at higher risk.
In advanced stages, a cure is less likely. A combination of surgery and chemotherapy/targeted therapy can prolong life and alleviate symptoms. Unfortunately, ovarian cancer in advanced stages is often resistant to chemotherapy and targeted therapy (2, 3). Overall, the five-year relative survival rate for advanced stages is approximately 10-40%. The degree of differentiation or dedifferentiation of ovarian cancer is determined pathologically in grading and helps to assess the aggressiveness of the disease. Grading is a parameter for predicting survival time and influences the treatment strategy. High-grade tumors are generally more aggressive and have a poorer prognosis, which is why early diagnosis and more intensive therapy are crucial. The treatment of ovarian cancer consists of a combination of surgery, chemotherapy, targeted therapies, and immunotherapies, depending on the stage and molecular characteristics of the tumor.
Chemotherapy is the standard treatment for advanced ovarian cancer (stages III and IV) or after surgery to eliminate micrometastases that cannot be removed surgically. A combination therapy of carboplatin and paclitaxel has proven to be very effective in the treatment of ovarian cancer. In addition, targeted therapies have been developed in recent years that specifically target molecular changes in ovarian cancer. This is particularly important for resistance to cisplatin or paclitaxel. PARP inhibitors (olaparib and niraparib) are particularly effective in patients with BRCA1 or BRCA2 mutations, which impair the repair of DNA damage. These drugs prevent the repair of DNA damage in cancer cells, leading to cell death. Bevacizumab is an inhibitor of vascular endothelial growth factor (VEGF), which blocks neoangiogenesis and thus prevents the tumor from spreading (1, 4).
Immunotherapy is playing an increasingly important role in ovarian cancer. In many cases, it has not yet achieved the same standardized application as in other cancers, such as lung cancer or melanoma. Immunotherapy aims to activate or strengthen the immune system to help the body recognize and destroy cancer cells. It works in various ways, for example, by blocking immune checkpoints that normally prevent the immune system from attacking tumors, or by introducing genetically modified immune cells or cancer vaccines. Checkpoint inhibitors such as pembrolizumab block specific signaling pathways in the immune system. This therapy may be promising for certain genetic changes (e.g., microsatellite instability) (5).
In ovarian cancer, specific transcription factors play an important role in carcinogenesis and tumor progression by regulating the expression of downstream genes for malignant cell growth, division, and survival. Some of these transcription factors contribute causally to the development and progression of ovarian cancer as oncogenic drivers (TP53, c-MYC, NF-κB, and E2F) (6, 7). Other transcription factors have a more tumor growth-supporting effect and influence the disease course (SOX17, FOXM1, PAX8) (7, 8).
The transcription factor activator protein 1 (AP-1) can be regarded as a non-oncogenic driver gene. Although it is involved in tumor development, it is considered more of a modulatory element that can influence the activity of other critical genes. It thus regulates cell proliferation, apoptosis, differentiation, invasion, and metastasis, which can be crucial for the progression of cancer. AP-1 is not a single protein, but a dimeric transcription factor consisting of proteins from the FOS and JUN families (c-FOS, FOSB, FOSL1/2, c-JUN, JUNB, and JUND) that recognize DNA sequences via the basic leucine zipper (bZIP) domain and bind to so-called TPA response elements (TRE) on the promoter sequences of downstream genes, activating their transcription. The composition (c-JUN/c-FOS vs. JUNB/FOSL1, etc.) determines the target gene selection and thus the functional effects (9, 10). AP-1 regulates numerous genes that play a role in tumor progression, such as MMP2, MMP9, CCND1, BCL-2, BCL-XL, VEGF, FASL, IL-8, CDH1, etc. (11-17). AP-1 contributes to the aggressiveness of ovarian carcinomas by supporting their ability to metastasize, resist apoptosis, and proliferate. In this respect, AP-1 plays a central role in the molecular signature of many ovarian carcinomas (12, 18, 19).
Some of the AP1-regulated target genes influence the efficacy of PD-L1 inhibitors either by promoting inflammatory processes or by directly influencing the immune response. IL-8, VEGF, FASL, and BCLXL are particularly important for immunotherapy with PD-L1 inhibitors, as these genes influence the tumor microenvironment in a way that can limit the immune response (20-25). These genes contribute to the creation of an immunosuppressive microenvironment that could impair the effect of PD-L1 inhibitors. A combination of PD-L1 inhibition with other targeted therapies that address these molecular targets, or even with standard therapy such as carboplatin, which increases the neoantigen load and thus makes the tumor more susceptible to immunotherapies, could increase the effectiveness of immunotherapy by making the tumor microenvironment more “permeable” to immune cells and making tumor cells more susceptible to an immune response.
The aims of the present investigation were, first, to investigate the prognostic significance of members of the FOS and JUN families, alone and in combination, for the overall survival of patients with ovarian carcinoma. Second, we used the FOS/JUN expression profiles and combined them with the tumor infiltration rates of 11 cell types of the innate and adaptive immune system. Specific FOS/JUN expression and tumor infiltration patterns significantly correlated with a short survival of patients. These patterns may serve for diagnosis to identify high-risk patients and for therapy to select individual patients for immunotherapies.
Patients and Methods
Survival time analysis. Kaplan-Meier statistics were used to calculate the survival times of patients with cancer. The survival probabilities were examined in relation to clinical or laboratory parameters of the individual tumors using the KM Plotter algorithm (26). To avoid type I errors of multiple comparisons, the false discovery rate (FDR) (27) was set to a cut-off of 5%. The database of the KM Plotter is based on data from The Cancer Genome Atlas (TCGA) and consists of the mRNA expression from RNA-sequencing of 373 ovarian carcinomas.
In addition to the RNA-sequencing-based mRNA expression of FOS, FOSB, FOSL1, FOSL2, JUN, JUNB, and JUND, tumor infiltration by different immune cell types was included in the analysis. The cell types of the innate immune system examined were basophilic granulocytes, natural killer cells, and eosinophilic granulocytes. However, the cell types of the adaptive immune system were B-cells, CD4+ memory T cells, CD8+ cytotoxic T cells, regulatory T cells, type 1 helper T cells, and type 2 helper T cells. Mesenchymal stem cells are not immune cells in a strict sense. However, since they support immune reactions, they were also included in the analysis.
Hierarchical cluster analysis. Hierarchical cluster was performed using the Ward method implemented in WinSTAT (Kalmia, CA, USA)
Results
The relevance of the transcription factor AP-1 for the overall survival time of patients with ovarian cancer was investigated. For this purpose, the mRNA expression of members of the FOS gene family (FOS, FOSB, FOSL1, and FOSL2) and the JUN gene family (JUN, JUNB, and JUND) in biopsies from 373 ovarian carcinomas stored in the TCGA-based KMPlotter database (www.kmplot.com) was analyzed using Kaplan-Meier statistics.
Significant correlations (p<0.05, FDR ≤5%) between increased expression of these genes and shortened survival time were found for JUNB and the combinations of JUNB with FOSB, FOSL1, and FOSL2 (Table I). All other correlations with FOS and JUN members individually or in combination were not statistically significant. All possible combinations were tested because the transcription factor AP-1 acts as a dimer, which always consists of one FOS and one JUN monomer. Therefore, the combined expression of these genes is more important than the expression of a single gene.
Relationship between expression of FOS and JUN and shorter overall survival duration of 373 patients with ovarian carcinoma.
As an example, the overall survival curves for the combined gene expression of FOSL2 and JUNB are shown in Figure 1A.
Overall survival duration of patients with ovarian carcinoma. The survival curves generated using Kaplan-Meier statistics show that a high expression of FOSL2 and JUNB is correlated with shorter survival probabilities in (A) the entire collective of 373 tumors and (B) a subset of 319 Grade-3 tumors. The combined mean expression of FOSL2 and JUNB, along with increased counts of (C) NK cells or (D) CD8+ T cells, also results in shorter overall survival duration. Statistical significance was based on the criteria p<0.05 and FDR ≥5%. Survival curves were generated using the Kaplan-Meier Plotter (www.kmplot.com).
Since tumor differentiation is an important prognostic marker for ovarian cancer, we analyzed the grading in relation to the expression of the FOS/JUN members. This showed that grade 3 tumors with high JUNB expression alone or in combination with FOSB, FOSL1, or FOSL2 were also significantly associated with shorter survival times (Table II). The other differentiation levels (grades 1, 2, or 4) either showed no significant results or the number of tumors with these gradings was too small for calculation. No correlations with tumor staging as a second clinically relevant prognostic factor were found. The survival curves for the averaged gene expression of FOSL2 and JUNB in grade 3 tumors are shown as an example in Figure 1B.
Relationship between expression of JUNB and its FOS partners and overall survival duration of 319 patients with ovarian carcinoma grade 3.
As the treatment outcomes by classical therapies (surgery, chemotherapy, and radiotherapy) are not satisfying, the potential of new immunotherapies has been recently studied (5, 28). We therefore investigated the association between FOS/JUN family members and tumor infiltration by different innate and adaptive immune cell types. Specifically, we analyzed high JUNB expression alone and in combination with FOSB, FOSL1, or FOSL2 in relation to immune cell counts within the tumors. The results were plotted as a matrix and subjected to hierarchical cluster analysis. The cluster image map in Figure 2 shows that three clusters of immune cell types appeared. Cluster 1 mainly consisted of decreased cell counts of CD8+ cytotoxic T-cells, regulatory T-cells, and natural killer cells, while cluster 3 contained mainly enriched fractions of immune cells, viz., type 2 T helper cells and basophilic granulocytes. The clustered heatmap in Figure 2 revealed three distinct immune cell clusters. Cluster 1 was primarily characterized by reduced counts of CD8+ cytotoxic T cells, regulatory T cells, and natural killer cells, whereas cluster 3 was mainly associated with increased proportions of immune cells, particularly type 2 helper T cells and basophilic granulocytes. High expression of FOS/JUN members together with decreased immune cell counts in cluster 1 and enriched tumor infiltration of immune cells in cluster 3 correlated significantly with shorter survival times of patients with ovarian carcinoma (p<0.05; FDR ≤5%). The immune cells assembled in cluster 2 mostly did not show an influence on the survival of patients. The distribution of cell types belonging to either the innate or adaptive immune system was independent of the clustering into three clusters.
Hierarchical cluster analysis of Kaplan-Meier analyses of JUNB mRNA expression alone and in combination with FOSB, FOSL1, or FOSL2 expression in 319 ovarian carcinomas. Shown are significant correlations between high mRNA expression in tumors and worse overall patient survival (p<0.05; FDR ≤5%). The high expression of these AP-1 binding partners was combined with increased or decreased counts of immune cells of the innate or adaptive immune system. The cell counts were taken as parameters for tumor infiltration by immune cells. Three clusters were obtained: Cluster 1 contained mainly decreased counts of immune cells, while Cluster 3 contained mainly increased counts of immune cells. In Cluster 2, enrichment or reduction of immune cells did not influence the survival of patients.
Kaplan-Meier survival curves for FOSL2/JUNB combined with NK cells, as an example of a cell type of the innate immune system, and combined with CD8+ cytotoxic T-cells, as an example of a cell type belonging to the adaptive immune system, are shown in Figure 1C and D.
Discussion
AP-1 is a dimeric transcription factor consisting of a member of the JUN family (JUN, JUNB, and JUND) and a member of the FOS family (FOS, FOSB, FOSL1/FRA-1, and FOSL2/FRA-2). AP-1 binds DNA via a basic leucine zipper domain and controls the transcription of downstream genes. JUN proteins can form homo- and heterodimers, while FOS proteins can only form heterodimers with members of the JUN family. The exact dimer composition determines binding affinity and target gene spectrum (29, 30).
A key finding of our analysis is that JUNB was a prognostic factor for ovarian cancer. High JUNB expression, especially in combination with FOSB, FOSL1, or FOSL2, was significantly associated with shortened overall survival. Other FOS or JUN members (alone or in combination) showed no significant effect. The fact that only certain JUNB-containing dimers were prognostically relevant for the survival of patients with ovarian carcinomas indicates the specificity of our results and that these are not merely random signals.
These results suggest that the composition of AP-1 dimers determines its different functions and that AP-1 dimers containing JUNB in particular are important for ovarian cancer (31, 32). JUNB is known to promote tumor proliferation and block its differentiation. It also modulates inflammatory processes, which overall promote the aggressiveness of tumors. This view is also supported by the fact that the negative prognostic effect of JUNB (alone and in combination with FOSB/FOSL1/FOSL2) was also detectable in aggressive grade 3 tumors. JUNB thus appears to be a factor in the development of a dedifferentiated, aggressive phenotype leading to a short survival prognosis. In ovarian cancer, the AP-1 dimer consisting of JUNB and FOSL1 has been described not only in connection with tumor progression, but also with chemoresistance (33). Furthermore, the AP-1 dimer consisting of JUNB and FOSL2 is involved in inflammatory and tumor-promoting programs of ovarian cancer (34, 35). In the classic 3-stage model of carcinogenesis (initiation, promotion, and progression), JUNB-containing AP-1 dimers appear not to be early initiators, but rather later progression factors, e.g., invasion and metastasis. AP-1 can therefore be understood as a “stress integrator” rather than a classic oncogenic driver (36).
In late stages of tumor evolution, AP-1 also contributes to the remodeling of the tumor microenvironment and suppression of cytotoxic immune responses (37-39). In the second part of our study, we therefore analyzed the correlation between the expression of FOS/JUN members and immune cell infiltration. We showed that high JUNB expression (alone or in combination) is associated with two prognostically unfavorable patterns in immune status: In cluster 1, reduced cell counts of CD8+ cytotoxic T cells, natural killer cells, and regulatory T cells were associated with shortened survival time. This suggests an immune-cold tumor microenvironment. In contrast, immune cells (i.e., type 2 T helper cells and basophilic granulocytes) were elevated in cluster 3 and thus immunologically active, but the effect was apparently tumor-promoting. A type 2 T helper cell-dominated tumor microenvironment appears to be tumor-promoting. Immune cells in cluster 2 showed no significant results and were neutral for survival. The data suggest that JUNB-containing AP-1 dimers are associated with functional reprogramming of the tumor microenvironment, which promotes both immune evasion and tumor-promoting immune responses. The fact that cell types of the innate and adaptive immune systems were distributed independently of clustering suggests that functional programs (e.g., altered cytokine and chemokine production) were more important than the pure immune cell class.
While the TCGA data are a highly valuable source, some limitations may also be considered. The analysis is based on retrospective TCGA data and Kaplan-Meier correlations. The correlations found are not causal, and other factors not considered here may also contribute to the observed effects. Future studies should therefore examine not only mRNA expression but also protein expression, posttranslational modifications (e.g., phosphorylation), and functional analyses (e.g., DNA-binding activity of AP-1). Regarding immune status, attention should be paid not only to the presence of immune cells but also to their activation or exhaustion status. Ovarian carcinoma is usually treated with platinum derivatives (cisplatin, carboplatin). Cisplatin is known to induce AP-1 expression, which contributes to the development of cisplatin resistance (40, 41). However, cisplatin-induced DNA damage increases the neoantigen load in tumors. This improves the chances of inducing immunogenic cell death (42-44). A combination therapy of cisplatin and immunotherapy could therefore be a promising treatment strategy (45). Furthermore, immunotherapeutic strategies could prevent the functional exhaustion of CD8+ cytotoxic T cells in the tumor, “heat up” cold tumors, and counteract the skewing of the immune status caused by type 2 T helper cells. Thus, JUNB-containing AP-1 dimers appear to be a hub between the chemotherapy-induced stress response and the immune microenvironment of the tumor. This point of view is supported by the fact that genes that are important for the tumor immune response are transcriptionally regulated by AP-1. Some examples are: The proinflammatory interleukin-8 (IL-8) is responsible for recruiting immune cells into the tumor microenvironment. High IL-8 levels can inhibit the T-cell response and negatively affect the tumor microenvironment for immune cells (46). Transforming growth factor β (TGF-β) plays a key role in immune evasion and the creation of an immunosuppressive microenvironment by suppressing the function of immune cells, particularly T cells. It contributes to a poor prognosis in tumors, as it can reduce the activity of cytotoxic T cells (46). The adhesion molecule CD44 not only influences the hematogenous metastasis of tumor cells, but also hinders the penetration of immune cells into the tumor (47). Vascular endothelial growth factor (VEGF) not only promotes the formation of new blood vessels in the tumor but also impairs the recruitment of immune cells into the tumor microenvironment. High VEGF levels can hinder an immune response by making it difficult for T cells to access the tumor (48). The Fas ligand is a key molecule of the receptor-driven pathway of apoptosis. In tumors, it supports the elimination of T cells (49) and thereby contributes to the undesirable protection of tumor cells. The anti-apoptotic BCL-2 belongs to the mitochondrial pathway of apoptosis and also confers resistance of tumors to both chemo- and immunotherapy (49). These few examples may provide mechanistic explanations for the short survival of patients with ovarian carcinoma and high AP-1 expression in their tumors.
In conclusion, the combination of AP-1 expression and immune cell profile provides a more differentiated risk assessment for (i) “immune-cold” tumors with high JUNB/FOSL1/FOSL2 expression, which have a particularly poor prognosis; and (ii) “Immune-skewed” tumors (type 2 T helper cell/basophilic granulocyte dominance), which also have a poor prognosis. These findings could help identify patients with high AP-1 activity and an unfavorable immune profile to select high-risk patients for more intensive therapy. In this context, our results may provide a biological rationale for the use of combination therapies. It should be noted that chemotherapy (e.g., cisplatin) activates AP-1, which can stress tumor cells and thus have a positive therapeutic effect, but in AP-1-containing tumors, it could also promote immune evasion, which has a negative effect. Whether the combination of chemotherapy and immunotherapy has a synergistic or additive effect remains to be seen. Overall, our results provide a testable mechanistic hypothesis for combination therapy involving chemotherapy with other checkpoint inhibitors or other immune-activating approaches in tumors with high JUNB dimers. It would also be interesting to investigate whether JUNB-containing AP-1 dimers can serve as additional prognostic markers for ovarian cancer, in addition to those already available, and whether AP-1 inhibition (e.g., by MAPK/JNK inhibitors) can enhance the effects of immunotherapy.
Acknowledgements
Ednah Ooko is funded by the NIH Intramural Research Program of the National Institute of Health (NIH), National Cancer Institute (NCI) and Center for Cancer Research (Bethesda, MD, USA).
Footnotes
Authors’ Contributions
MD performed the analysis, EO reviewed and edited the manuscript, TE supervised and conceptualized the project, and TE and JCB wrote the article.
Conflicts of Interest
The Authors declare no competing interests in relation to this study.
Artificial Intelligence (AI) Disclosure
No artificial intelligence (AI) tools, including large language models or machine learning software, were used in the preparation, analysis, or presentation of this manuscript.
- Received February 25, 2026.
- Revision received March 5, 2026.
- Accepted March 6, 2026.
- Copyright © 2026 The Author(s). Published by the International Institute of Anticancer Research.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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