Can activator protein-1 transcription factors be monitored in the maternal circulation to predict set on labor?

Toghrul Yahyayev; Tugce Senturk Kirmizitas; Ali Benian; Tuba Gunel

doi:10.5468/ogs.23288

Obstet Gynecol Sci > Volume 68(2); 2025 > Article

Yahyayev, Kirmizitas, Benian, and Gunel: Can activator protein-1 transcription factors be monitored in the maternal circulation to predict set on labor?

Original Article

Maternal-Fetal Medicine

Obstetrics & Gynecology Science 2025;68(2):139-147.

Published online: February 12, 2025

DOI: https://doi.org/10.5468/ogs.23288

Can activator protein-1 transcription factors be monitored in the maternal circulation to predict set on labor?

Toghrul Yahyayev, MD¹, Tugce Senturk Kirmizitas, PhD², Ali Benian, MD¹, Tuba Gunel, PhD²

¹Department of Obstetrics and Gynecology, Istanbul University - Cerrahpaşa, Cerrahpaşa Faculty of Medicine, Istanbul, Türkiye

²Department of Molecular Biology and Genetics, Faculty of Science, Istanbul University, Istanbul, Türkiye

Corresponding author: Tuba Gunel, PhD, Department of Molecular Biology and Genetics, Faculty of Science, Istanbul University, Beyazıt, Istanbul 34452, Türkiye, E-mail: gunel@istanbul.edu.tr

Received December 10, 2023 Revised September 6, 2024 Accepted February 2, 2025

Articles published in Obstet Gynecol Sci are open-access, distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Objective

We aimed to compare gene expression levels in myometrial tissues and serum from pregnant women undergoing cesarean section (CS) with and without uterine contractions. The myometrial activator protein-1 (AP-1) transcription factor family (JUN, FOS, and fos-related antigen-2 [FOSL2]) was evaluated as a contraction-related marker in maternal circulation to predict labor timing.

Methods

Samples were collected from pregnant women undergoing CS. Uterine contractions were observed in the experimental group (n=10) but not in the control group (n=10). Gene expression of JUN, FOS, and FOSL2 was analyzed in serum and myometrial samples using droplet digital polymerase chain reaction, and statistical analysis was performed using GraphPad software (GraphPad Software, San Diego, CA, USA).

Results

Given the non-normal data distribution, JUN, FOS, and FOSL2 gene expression levels increased in the CS group with uterine contractions. However, this increase was not statistically significant in either tissue or serum samples. Nevertheless, the correlation of JUN messenger RNA expression between maternal circulation and myometrial tissue was statistically significant in the CS group with contractions (P<0.01).

Conclusion

This is the first study to investigate AP-1 transcription factor expression in matched tissue and serum samples in relation to uterine contractility. The increased expression of JUN, FOS, and FOSL2 in the CS group with contractions suggests these genes may play a key role in initiating or propagating human labor, indicating that contraction-associated AP-1 could serve as a biomarker for labor timing.

Keywords: Activating transcription factor 1; Gene expression; Labor onset; Uterine circulation

Introduction

Although many factors contribute to the onset of labor, hormonal influences, such as the functional withdrawal of progesterone, mechanical stretch, and a cascade of inflammatory processes, as well as transcription factors (TFs), are critical in labor induction. Physiologically, the uterus must remain quiescent (non-contractile) throughout pregnancy and then transition to a contractile state immediately before labor to expel the fetus [1,2]. Accumulating evidence supports the concept that term labor is modulated by signals secreted from both fetal and maternal uterine tissues, such as the decidua and myometrium [3]. The myometrium is the muscular layer of the uterus that supports its structural integrity and plays a dual role in regulating the switch between uterine contraction (UC) states during pregnancy and labor [4].

The smooth muscle cell (SMC) layer of the myometrium undergoes both structural and functional phenotypic transformations that enable the forceful labor contractions required to deliver a mature fetus [5]. Myometrial contractility is primarily regulated by the balance between factors that maintain uterine quiescence and those that promote uterine contractility [6]. The progestational hormone progesterone (P4) and steroid hormone estradiol (E2) play opposing roles in regulating uterine function; P4 supports fetal growth and development by preventing myometrial contractions, whereas E2 promotes myometrial activation [7].

Ribonucleic acid (RNA) sequencing data from myometrial tissues in human and rodent gestational models have shown a significant increase in myometrial transcript levels during the transition from quiescence to contractility [8]. Evidence for the role of TFs in this process includes an increase in the expression of contractility-associated genes, such as connexin-43 (Cx43), preceding term labor [9]. For example, activator protein-1 (AP-1) is a key transcriptional regulator of pathways involved in the production of proinflammatory cytokines and mediators that contribute to labor induction. The AP-1 family of TFs (JUN, FOS, and fos-related antigen-2 [FOSL2]) primarily regulates Cx43 transcription, which is essential for connecting individual SMCs into an organized three-dimensional syncytium capable of generating synchronized labor contractions [10]. Cx43 expression and gap junction formation increase profoundly before labor, making Cx43 a key labor-associated gene [11]. As a hormonal mediator, P4 exerts its anticontractile effects through the inhibitory interaction of progesterone receptors with AP-1 TFs [12].

AP-1 TFs exhibit differential affinities for DNA binding; thus, the formation of homo- or heterodimers among family members determines their transcriptional activity [13]. For example, JUN proteins can exist as either homo- or heterodimers, whereas FOS proteins do not form homodimers but instead heterodimerize with JUN, activating transcription factor family, or musculoaponeurotic fibrosarcoma family proteins [14]. Nadeem et al. [15] proposed that certain members of the AP-1 family, including JUN, are consistently present in SMCs throughout gestation at relatively stable levels, whereas other AP-1 members, such as JUND, FOS, and FOSL2, are markedly upregulated in the human myometrium. Although this study substantially contributed to our understanding of AP-1 TFs, it did not investigate their presence in maternal circulation [15].

This preliminary study aims to compare AP-1 TF levels in patient-matched serum and myometrial samples to determine their potential role in predicting labor onset. Furthermore, it explores epigenetic influences on labor timing, which may be addressed in future research.

Materials and methods

1. Study design and participants

This study included 20 pregnant women recruited between October 2018 and March 2019. Participants met the following inclusion criteria: gestational age of 37 weeks or more, maternal age between 18 and 35 years, no history of smoking or alcohol use, absence of chronic diseases, no continuous drug use, no preterm rupture of fetal membranes, and no pregnancy complications, such as polyhydramnios or placenta previa. Women with evidence of local or systemic inflammation or uterine distension were excluded to ensure a homogeneous study population.

In Türkiye, labor is defined by the Turkish Ministry of Health as the process of delivering a live baby between 37 and 42 completed weeks of pregnancy, calculated from the last menstrual period. This includes spontaneous vaginal delivery with UCs or delivery via cesarean section (CS) performed for appropriate medical indications. Active labor is characterized by regular UCs and cervical dilation, both essential signs of labor progression. CSs may be performed during active labor if vaginal delivery is not possible for medical reasons.

Participants were divided into two groups based on the presence or absence of UCs. The contraction group consisted of 10 pregnant women who underwent CS during active labor. Active labor in these participants was confirmed using cardiotocography recordings, which showed either four or more contractions within 20 minutes or eight or more contractions within 60 minutes.

The non-contraction group consisted of 10 pregnant women who underwent elective CS without any evidence of UCs, as confirmed by cardiotocography recordings.

This study was approved by the Clinical Research Ethics Committee (decision number 83045809, dated 2018/06/02). All patients provided informed consent before participation.

2. Biological samples and total RNA extraction

Myometrial tissue (approximately 1 cm³) from the upper Munro-Kerr incision and peripheral blood were collected during CS. Tissue samples were stored at −80°C after being kept at 4°C for 24 hours. Blood samples were centrifuged (937 g×20 minutes; 4°C), after which the serum was aliquoted and stored at −80°C. RNA was extracted using the mirVana™ PARIS kit (Ambion; Thermo Fisher Scientific, Inc., Waltham, MA, USA) for tissue samples and PureLink™ RNA Mini Kit (Invitrogen; Thermo Fisher Scientific, Inc.) for blood samples, according to the manufacturer’s protocol. RNA concentration and purity were assessed using a NanoDrop spectrophotometer (Thermo Fisher Scientific, Inc.), and samples were stored at −80°C for reverse transcription polymerase chain reaction (PCR).

3. cDNA synthesis

cDNA was synthesized using the iScript™ Reverse Transcription Supermix (Bio-Rad, Hercules, CA, USA) according to the manufacturer’s instructions. Briefly, cDNA was synthesized in 20-μL reactions containing 4 μL of 5×iScript™ (Bio-Rad) reaction mix and 10 μL of nuclease-free water. The reaction contained 1 μg of RNA, and cDNA samples were diluted to 50 ng/μL. Primers were designed using Primer3 software (Whitehead Institute for Biomedical Research, Cambridge, MA, USA). Gene sequences were retrieved from National Center for Biotechnology Information, and all oligonucleotides were tested for specificity using Primer-BLAST (National Center for Biotechnology Information, Bethesda, MD, USA). The primer sequences, optimal annealing temperatures, and amplicon sizes of the genes used in this study are listed in Supplementary Table 1.

4. Droplet digital PCR

Droplet digital PCR was performed according to the manufacturer’s instructions using the QX200™ Droplet Digital PCR System and the QX200™ Droplet Generator Instruction Manual (Bio-Rad, Hercules, CA, USA). Briefly, each 20-μL reaction contained 1×EvaGreen droplet digital PCR Supermix (Bio-Rad) (10 μL), 200 nM gene-specific forward primers, 100 nM gene-specific reverse primers, and 2 μL of cDNA sample (approximately 100 ng). Droplets were generated using a QX200™ Droplet Generator (Bio-Rad). Cycling conditions using the EvaGreen ddPCR Supermix (Bio-Rad) assay were programmed as follows: 1×(95°C for 5 minutes), 40×(95°C for 30 seconds; 57°C for 1 minute), 1×(4°C for 5 minutes; 90°C for 5 minutes), and ramp rate: 2°C/s. Immediately after endpoint amplification, the fluorescence intensity of individual droplets was measured using a QX200™ Droplet Reader (Bio-Rad). Data analysis was performed using QuantaSoft™ droplet reader software (Bio-Rad). Positive and negative droplet populations were detected automatically.

5. Bioinformatic analysis

All statistical analyses were performed using GraphPad Prism version 9.2 (GraphPad Software Inc., La Jolla, CA, USA). D’Agostino and Pearson’s normality tests were performed to determine whether the data followed a normal or non-normal distribution. For non-parametric comparisons between groups, the Mann-Whitney U-test was used. The results are presented as mean±standard error of the mean. Receiver operating characteristic (ROC) curves were generated, and the area under the curve (AUC), sensitivity, and specificity were calculated to evaluate the diagnostic value of candidate messenger ribonucleic acids (mRNAs). Correlation analysis was performed using Pearson’s correlation test. P<0.05 was considered statistically significant. The datasets used and analyzed in this study are available from the corresponding author upon reasonable request.

6. Gene ontology (GO) and pathway enrichment analysis

GO is a tool used for gene annotation through a structured, controlled vocabulary that includes three main categories: molecular function, biological process, and cellular components 16]. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to associate related gene sets with their corresponding pathways [17]. database for annotation, visualization, and integrated discovery (DAVID), an integrated data mining tool, was used for gene list analysis [18]. GO annotation and KEGG pathway enrichment analyses were conducted for these three genes using DAVID.

Results

Using Google Scholar and the National Center for Biotechnology information, we identified AP-1 TFs correlated with UCs. Following a literature review, three candidate genes-JUN, FOS, and FOSL2-were selected for further evaluation. We measured the expression levels of these AP-1 TFs in myometrial tissue and serum samples from pregnant women. All raw gene expression data were normalized to glyceraldehyde-3-phosphate dehydrogenase, which was used as an internal control.

1. AP-1 TF mRNA expression analysis in tissue and serum

The expression levels of JUN, FOS, and FOSL2 in the myometrium of women in labor were 1.5-, 2.7-, and 1.4-fold higher in the CS with UCs group than in the CS without UC group (Fig. 1). Similarly, JUN, FOS, and FOSL2 expression levels in the serum of women in labor were 1.1-, 1.4-, and 1.6-fold higher in the CS with UC group than in the CS without UC group (Fig. 2).

Statistical analysis using the non-parametric Mann-Whitney U-test showed that JUN, FOS, and FOSL2 gene expression in both tissue and serum samples did not exhibit a statistically significant difference between the CS with UC and CS without UC groups.

2. ROC curve analysis

ROC curve analysis was performed to assess the diagnostic value of the candidate genes. The AUC for each gene was greater than 0.500. Among these genes, FOS (AUC, 0.7) in tissue samples demonstrated potential as a predictive biomarker. The AUC values for the other genes were less than 0.700 (Fig. 3).

3. Correlation analysis between tissue and serum

This analysis investigated whether gene expression levels in myometrial tissue correlated with those in serum. The positive and negative correlations are shown in Fig. 4. A negative correlation was observed between FOS and FOSL2 in tissue and serum samples, whereas a positive correlation was observed between JUN expression in tissue and serum samples. Although the JUN correlation was statistically significant (P<0.01) in the CS with UC group, no significant correlation was observed in the CS without UC group (P>0.05).

4. GO terms and KEGG pathway enrichment analysis of AP-1 TF mRNA

The results of GO analysis demonstrated that the three genes were mainly enriched in biological processes, including response to muscle stretch, positive regulation of transcription from the RNA polymerase II promoter, cellular response to reactive oxygen species, cellular response to cadmium ions, response to cyclic adenosine monophosphate, and response to cytokines. Cellular component analysis indicated that AP-1 genes were significantly enriched in the RNA polymerase II TF complex, TF AP-1 complex, and chromatin. For molecular functions, these genes were primarily associated with chromatin-binding transcriptional activator activity, RNA polymerase II transcription regulatory region sequence-specific binding, TF activity, sequence-specific DNA binding, and receptor-regulated Sma- and Mad-related protein binding (Table 1). KEGG pathway analysis revealed that these genes were associated with osteoclast differentiation (hsa04380) and amphetamine addiction (hsa05031) (Table 2).

Discussion

Under normal physiological conditions, labor is initiated by a synchronized interplay of multiple mechanisms, including functional progesterone withdrawal and uterine stretching 19,20]. Because of ethical considerations and limitations in studying human pregnancy, much of the current understanding of myometrial contractility is derived from rodent and other model organism studies. These studies have demonstrated that the myometrium undergoes extensive structural and functional changes throughout pregnancy and labor [21]. At the end of pregnancy-whether at term or preterm-an increase in contraction-associated proteins transforms the quiescent myometrium into a highly contractile tissue capable of generating strong, rhythmic labor contractions, marking the onset of parturition [22]. This phenotypic transformation is driven by multiple mechanical, endocrine, and proinflammatory signals initiated by both fetal and maternal tissues 23]. Weak or insufficient uterine contractility can delay labor onset and impair labor progression, posing considerable risks to both the mother and fetus [24-26]. A comprehensive understanding of the molecular mechanisms governing labor initiation is therefore crucial for preventing preterm labor.

AP-1 is among the most extensively studied TF families involved in regulating myometrial contractility. Several labor-associated genes, including CX43, prostaglandin-endoperoxide synthase 2, and oxytocin receptor, contain AP-1 dimer binding sites in their promoter regions across multiple species, including mice, rats, and humans [22]. According to the literature, JUN homodimers bind to regulatory regions in the quiescent myometrial genome before being replaced by FOS-containing heterodimers. JUN-FOS heterodimers subsequently trigger gene transcription necessary for myometrial contractility and labor timing regulation [27,28].

In human studies, Lim and Lappas [29] found that c-Fos and JunB mRNA and protein expression increased, FosB mRNA and protein expression remained unchanged, and JunD mRNA and protein expression decreased during term labor. Roh et al. [30] found that c-Jun expression increased during labor. Geimonen et al. [31] found that phosphorylated c-Jun levels increased in the human myometrium during the onset of labor. Lappas et al. [32] found that phosphorylated c-Jun increased, whereas the non-phosphorylated form remained unchanged, in the fetal membranes near the internal os in term women who were not in labor and underwent elective CS. Nadeem et al. [15] found that in term pregnant women, there was no significant increase in Jun and FOS proteins in the cytoplasm, but nuclear JUND, c-FOS and FOLS2 gene expression increased.

In the last decade, high-dimensional techniques, such as transcriptomics, proteomics, and metabolomics, have been used to explore the complex and dynamic processes modulated in tissue and maternal circulation prior to and during labor [33,34]. Single-cell gene signatures derived from uterine tissues can be evaluated in maternal circulation, providing a potential biomarker for monitoring changes in reproductive tissues during pregnancy. Single-cell RNA sequencing of the placenta and chorioamniotic membranes, as well as multiple placenta-derived single-cell signatures, are modulated with gestational age in maternal circulation, with specific signatures being altered in women experiencing term or preterm labor [35]. This study demonstrates the potential prognostic utility of single-cell signals produced by intrauterine tissues for monitoring labor status and pregnancy-related diseases. However, these studies did not assess changes in AP-1 TF levels in women undergoing labor at term compared to serum-matched controls.

This is the first study to investigate the expression levels of AP-1 TFs in matched tissue and serum samples. JUN, FOS, and FOSL2 gene expression increased, although the increase was not statistically significant. AP-1 is regulated at multiple levels, and FOSL2 is a member of the AP-1 family. FOSL2 plays a role in controlling cell growth and coordinating signaling balance within and outside the cell. FOSL2 forms a dimer with c-JUN/JUNB/JUND that binds to the AP-1 consensus site of target genes and induces their transcription. The heterodimer of c-FOS/c-JUN significantly stimulates FOSL2 promoter activity, leading to increased FOSL2 expression. By contrast, FOSL2 overexpression leads to the replacement of the c-FOS/c-JUN heterodimer by the c-JUN/FOSL2 complex, reducing transcriptional activity and indicating a negative feedback mechanism that regulates FOSL2 expression. Because of this feedback mechanism, the increased expression of FOSL2 may have led to decreased c-FOS and c-JUN levels, preventing us from obtaining statistically significant results [36]. GO analysis revealed that the biological pathways in which the three genes were significantly enriched were primarily related to labor initiation and uterine contractility. One such pathway is the cellular response to cadmium ions, which has recently been shown to be enhanced in amniotic fibroblasts during labor [37]. This study also demonstrated a statistically significant positive correlation between JUN mRNA expression levels in myometrial tissue and serum samples. Although our study involved a relatively small number of participants, it provides valuable insights into the potential for non-invasive monitoring of gene expression changes. These changes may help track shifts related to the impending onset of labor. Although the sample size may have limited the ability to detect statistically significant differences, the findings suggest promising directions for future research. Larger studies with more participants are essential to confirm these results, further investigate the role of AP-1 TFs in labor, and enhance the clinical application of these findings for predicting labor timing.

Supplementary Information

ogs-23288-Supplementary-Table-1.pdf

Notes

Conflicts of interest

The authors declare no conflicts of interest.

Ethical approval

This study was approved by the Clinical Research Ethics Committee (decision number 83045809, dated 2018/06/02).

Patient consent

All patients provided informed consent before participation.

Funding information

This study was funded by the Scientific Research Projects Coordination Unit of Istanbul University-Cerrahpaşa (Project ID: 30487).

Fig. 1

Box plots of AP-1 gene expression levels in myometrial tissue samples. (A) Expression levels of JUN mRNA. (B) Expression levels of FOS mRNA. (C) Expression levels of FOSL2 mRNA. Bar graphs presented as mean±standard error of the mean. ‘n’ values: (10) CS without UC and (10) CS with UC. CS, cesarean section; UC, uterine contraction; AP-1, activator protein-1; mRNA, messenger ribonucleic acid; FOSL2, fos-related antigen-2.

Fig. 2

Box plots of AP-1 gene expression levels in serum samples. (A) Expression levels of JUN mRNA. (B) Expression levels of FOS mRNA. (C) Expression levels of FOSL2 mRNA. Bar graphs presented as mean±standard error of the mean. ‘n’ values: (10) CS without UC and (10) CS with UC. CS, cesarean section; UC, uterine contraction; AP-1, activator protein-1; mRNA, messenger ribonucleic acid; FOSL2, fos-related antigen-2.

Fig. 3

ROC curves of tissue and serum gene levels. (A) Tissue: ①, ROC analysis of JUN (AUC, 0.55); ②, ROC analysis of FOS (AUC, 0.71); ③, ROC analysis of FOSL2 (AUC, 0.61). (B) Serum: ①, ROC analysis of JUN (AUC, 0.55); ②, ROC analysis of FOS (AUC, 0.51); ③, ROC analysis of FOSL2 (AUC, 0.65). ROC, receiver operating characteristic; AUC, area under the curve; FOSL2, fos-related antigen-2.

Fig. 4

Correlation between tissue and serum samples of the genes. (A) JUN. (B) FOS. (C) FOSL2. Pearson’s r was used to analyze correlations, with P-values indicated (P<0.01). FOSL2, fos-related antigen-2.

Table 1

GO analysis

GO term	Description	Count	P-value
BP
GO: 0035994	Response to muscle stretch	2	2.1×10-3
GO: 0045944	Positive regulation of transcription by RNA polymerase II promoter	3	3.9×10-3
GO: 0034614	Cellular response to reactive oxygen species	2	3.9×10-3
GO: 0071276	Cellular response to cadmium ion	2	4.2×10-3
GO: 0051591	Response to camp	2	4.9×10-3
CC
GO: 0090575	RNA polymerase Iı transcription factor complex	3	3.5×10-5
GO: 0035976	Transcription factor AP-1 complex	2	4.8×10-4
GO: 0000785	Chromatin	3	2.6×10-3
GO: 0005667	Transcription factor complex	2	2.3×10-2
GO: 0005654	Nucleoplasm	3	3.7×10-2
MF
GO: 0003682	Chromatin binding	3	6.1×10-4
GO: 0001228	DNA-binding transcription activator activity, RNA polymerase II-specific	3	6.4×10-4
GO: 0003700	DNA-binding transcription factor activity	3	8.6×10-4
GO: 0070412	R-smad binding	2	2.1×10-3
GO: 0000978	RNA polymerase II core promoter proximal region sequence-specific DNA binding	3	4.1×10-3
GO: 0000981	Sequence-specific distal enhancer binding RNA polymerase II transcription factor activity	3	4.6×10-3

GO, gene ontology; BP, biological process; RNA, ribonucleic acid; CC, cellular component; AP-1, activator protein-1; MF, molecular function.

Table 2

KEGG pathway enrichment analysis

KEGG term	Description	P-value
hsa04380	Osteoclast differentiation	1.5×10-2
hsa05031	Amphetamine addiction	1.7×10-2
hsa05133	Pertussis	1.8×10-2
hsa05140	Leishmaniasis	1.9×10-2
hsa0466	B cell receptor signaling pathway	2.0×10-2
hsa05210	Colorectal cancer	2.1×10-2
hsa05235	PD-L1 expression and PD-1 checkpoint pathway in cancer	2.2×10-2
hsa04658	Th1 and Th2 cell differentiation	2.2×10-2
hsa05323	Rheumatoid arthritis	2.3×10-2

Term: KEGG pathway identification number and Description: name of the KEGG pathway.

KEGG, kyoto encyclopedia of genes and genomes; PD-L1, programmed death-ligand 1; Th1, T-helper type 1 cells.

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