Abstract
Globally, breast cancer is the most common cancer to affect women. There are different molecular and pathological factors that are involved in the uncontrolled proliferation of breast cancer cells. FOXN3 that is member of Forkhead box family proteins is well recognized for having a crucial role in different biological processes and is reported to be dysregulated in various malignancies. The studies to evaluate the significance of the FOXN3 gene in progression of breast cancer are still under progress. We in the current study aim to examine the FOXN3 gene expression in Indian breast cancer patients and find its clinical relevance. FOXN3 expression analysis using RT-PCR, immunohistochemistry, and western blotting was performed in tumor and normal tissue collected from 142 sporadic breast cancer patients. To identify the genetic aberrations in FOXN3 gene automated DNA sequencing was done. FOXN3 expression study revealed the elevated expression of FOXN3 mRNA in 61.26% of the cases whereas FOXN3 protein was seen to be overexpressed in 59.15% cases. Further, it was found that the elevated expression of FOXN3 mRNA was significantly correlated with the post-menopausal (p = 0.003) status and positive lymph node status (p = 0.049) of the patients. The FOXN3 protein expression also exhibited the significant association with menopausal status (p = 0.008), lymph node status (p = 0.001) and clinical stage (p = 0.018) of the patients. However, we did not find any mutation in the DNA binding domain of the FOXN3 gene in the Indian breast cancer cases. Our findings indicates that overexpression of FOXN3 gene in Indian breast cancer cases can have a potential role in breast cancer progression especially in advanced clinical stages.
Supplementary Information
Theonline version contains supplementary material available at 10.1038/s41598-025-98090-0.
Keywords: Breast cancer, FOXN3, mRNA, Expression
Subject terms: Cancer, Genetics
Introduction
Globally, breast cancer has contributed to a decline in women’s health, affecting more than 2.3 million females and with 685,000 breast cancer related mortalities in 20201. Despite tremendous efforts made by clinicians and researchers in the past few decades but there has been a steady rise in incidence of the disease. The diverse histopathology and different hormonal markers associated with breast cancer makes it challenging for timely diagnosis and efficacy of the treatment. Also, clinicopathological variables like lymph node status, tumor grade, tumor size etc. have vital role in determining the probability of clinical outcomes2–5.
Forkhead box protein N3 known as CHES1 (Checkpoint suppressor 1) is a protein that in humans is encoded by the FOXN3 gene. This gene is a member of the forkhead/winged helix transcription factor family, and its locus is 14q31.3-q32.11 in human6,7. FOXN3 majorly functions as a cell cycle regulator and a DNA damage checkpoint mediator. It regulates cell cycle progression by blocking cyclin-dependent kinases, causing an instantaneous halt to cell division, and enabling DNA repair and genomic stability8,9. Furthermore, FOXN3’s functions extend to transcriptional repression, where it works with a variety of cofactors to control gene expression10,11. FOXN3 exhibits a complex role in cancer, ironically operating as both a tumor suppressor and an oncogene. The primary aspects of FOXN3 tumor-preventing abilities are its control of the cell cycle and DNA damage response. It is essential for controlling unchecked cell proliferation because it inhibits cyclin-dependent kinases, which stops cells from moving through the cell cycle when DNA damage is found8,12,13. The oncogenic function of FOXN3 has also been reported in breast cancer where interaction of FOXN3 with SIN3A is mediated by NEAT1 thereby forming FOXN3-NEAT1-SIN3A complex in ER positive breast cancer cells14,15. Earlier studies have reported NEAT1 as unfavorable prognostic marker in breast cancer and can lead to growth and metastasis of breast cancer cells16.
NEAT1 is necessary for FOXN3 interactions with the SIN3A complex. In breast cancer cells (MCF-7), estrogen was found to increase NEAT1, while ERα (estrogen receptor alpha) knockdown inhibited this induction. The FOXN3-NEAT1-SIN3A complex was discovered to repress several genes, including GATA3 and TJP1, according to ChIP-Seq investigations (genes regulating cell maintenance and differentiation). It was discovered that ER signaling, the FOXN3-NEAT1-SIN3A complex, and the suppression of GATA3 and TJP1 expression by FOXN3 and NEAT1 function in an inhibitor feedback loop during the proliferation of mammary epithelial cells. In contrast, ER signaling decreased the growth signal when conditions were more favorable for differentiation or maintenance. The balance or decision (between differentiation or maintenance) of mammary epithelial cells was influenced by this regulatory system. There is a negative feedback loop between ER and the FOXN3-NEAT1-SIN3A complex in ER + breast cancer cells, in which ER transactivates NEAT1, which is assembled into the FOXN3-NEAT1-SIN3A complex, and this complex, in turn, trans-represses ER. NEAT1 is induced by estrogen and participates in transcription regulation by the FOXN3-NEAT1-SIN3A complex. Mammary epithelial cells must develop normally for this regulatory system to function properly. Breast cancer develops and spreads because of the upset in this equilibrium. The upregulated FOXN3-NEAT1-SIN3A complex encourages breast cancer cells’ EMT (Epithelial Mesenchymal Transition) in vitro and invasion and metastasis of breast cancer in vivo14,15.
Materials and methods
Study samples
This study contains 142 cases of clinically proven sporadic breast cancer in genetically unrelated females aged 20 to 79 years who did not receive chemotherapy or radiotherapy. During surgery, an aliquot of tumor and nearby normal tissues were placed in PBS, followed by RNA and formalin for further processing. The patients who volunteered to participate in the study provided written informed consent, and the clinicopathological criteria assessed at the time of diagnosis were obtained from the patient’s record while concerning the patients confidentially. The Institute Ethics Committee, AIIMS, New Delhi (IEC-849/03.12.2021) and the Institutional Ethics Committee, JMI, New Delhi (25/7/236/JMI/IEC/2019) provided ethical permission for this research. After getting ethical approval from both institutions, the clinical data of the patients was accessed, and all experiments were carried out from 02/03/2022 till November 2023 in accordance with the ethical guidelines and regulations. The clinical profiles of the patients enrolled in the study are provided in the supplementary file S2.
mRNA expression analysis
RNA was obtained from tissue samples that had been kept in RNA later at -80 ⁰C. Tissue was homogenized in TRIZOL (Invitrogen cat. No. 15596026) using the homogenizer, then phase separation, precipitation, and washing were performed according to the manufacturer’s procedure. To remove any DNA contamination, the obtained RNA pellet was dissolved in RNase-free water and treated with DNase. The purity and concentration of extracted RNA were determined using a NanoDrop spectrophotometer with a 260/280 ratio, with an ideal value of ~ 2 indicating high-purity RNA. For cDNA synthesis, RNA samples with a purity of 2.0 were employed. The Verso cDNA synthesis kit (cat. No. A48571) was used to create the cDNA, and 1000 ng of RNA was utilized per 20ul reaction17.
The cDNA was subjected to Real Time Polymerase Chain Reaction (RT-PCR) utilizing FOXN3-specific primers and ACTB as an internal control (S1). The RT-PCR reaction was carried out using the KAPA SYBR® FAST (cat no: KK4610) master mix and the manufacturer’s protocol.
DNA isolation
Genomic DNA was recovered by homogenizing 50–100 µg of tissue in tissue lysis buffer and incubating it at 45 ⁰C overnight18. Furthermore, DNA was extracted from tissue lysate using the phenol-chloroform technique. The acquired genomic DNA was analyzed qualitatively and quantitatively using gel electrophoresis on a 0.7% agarose gel. A NanoDrop spectrophotometer was used to confirm the DNA’s purity by measuring the A260/A280 absorbance ratio, with an ideal value of ~ 1.8 indicating high-purity DNA. Further studies were done using isolated genomic DNA with a purity of 1.8.
Immunohistochemistry
FOXN3 protein expression was examined through immunohistochemistry using FOXN3-specific antibody (PA5-63686). Formalin-fixed breast cancer tissue blocks were produced and sectioned on poly-L-lysine coated slides. The sections were deparaffinized with various grades of xylene before being rehydrated with a succession of ethanol. Endogenous peroxidase activity was inhibited using 0.3% hydrogen peroxide, and silver (Ag) was recovered by boiling in citrate buffer. The slides were Incubated overnight at 4 ⁰C with a 1:200 dilution of the primary antibody, followed by an hour at 37 ⁰C with the secondary antibody. The antibody binding site was visualized using 3,’’- diaminobenzidine (DAB), and the counter stain was Hematoxylin. Normal breast tissue served as the positive control, while sections processed using identical techniques except for the primary antibody incubation served as the negative control. Experts of histopathology rated the immunohistological staining as follows: (a) no expression- 0%, (b) mild expression- 1–10%, (c) moderate expression- 10–50%, and (d) high expression- > 50%19,20.
Western blotting
RIPA lysis buffer was used to isolate the total protein from tissue samples. The protein was quantified using the Bradford technique with varying BSA concentrations for the standard curve. On a 10% SDS gel, an equal amount of protein (30 µg) was resolved and transferred to a nitrocellulose membrane. One hour blocking of skimmed milk was followed by overnight primary antibody incubation for FOXN3 (PA5-106982) and the control gene beta actin (sc-47778). After three washes in TBST, the blots were incubated for one hour in appropriate HRP conjugated secondary antibodies. Clarity western ECL substrate (cat: 170–5060) was used for chemi-luminescence protein detection (Bio Rad).
Automated DNA sequencing
Mutations in DNA binging domain of FOXN3 were investigated. The exon 2 and 3 were amplified with specified primers (S1), and the PCR product was purified with the Qiagen MinElute PCR Purification kit (Cat. No.28004). Direct sequencing was performed on the amplified products at Macrogen Inc’’s South Korea lab utilizing both forward and reverse primers. Sequencing findings were analyzed using Clustal Omega software, with sequences aligned to the GRCh38 (hg38) reference human genome To rule out any contamination or erroneous results, the sequencing was repeated.
Screening of differentially expressed genes
NCBI-GEO datasets were queried using breast cancer as the key word to extract the mRNA expression profile. Further, the search was refined by using suitable inclusion criteria (i) the samples included in the datasets should be of Homo sapiens (ii) the data sets should be of “expression profiling by array” (iii) the availability of preprocessed and raw files (iv) the data set should have both tumor as well as healthy tissue (v) the dataset must have at least 25 samples. However, the datasets not having healthy control or non-human samples were excluded from the study. The DEGs (differentially expressed genes) were then identified between low and high FOXN3 expression subgroups defined by the median expression level of FOXN3 using “limma” R package considering (|log FC| > 0.5) and p < 0.05 to be statistically significant.
Pathway enrichment analysis
Significantly enriched pathways and Gene Ontology terms (for compiling top 10 significant pathway and GO terms corresponding prognostic signature) with p- value < 0.05 associated with the identified Differentially Expressed Genes (DEGs) were gathered using Enrichr web-based tool. For our analysis, we used reactome database and GO Biological Process, GO Molecular Function and GO Cellular Component libraries to compile the pathway and GO term data.
Survival analysis
GEPIA2 is an online available database that is helpful in pan cancer analysis to explore the gene expression, survival, methylation, and clinical profile in cancer. We examined the FOXN3 expression in the breast cancer patients included in the GEPIA2 data set and compared the survival data of the participants with low FOXN3 and high FOXN3 expression21.
Statistical analysis
Our molecular data and clinical factors were found to be statistically correlated using SPSS-IBM (version 22.0) and graph pad prism (9.0.2). The mRNA expression data in the study were expressed as mean ± standard error of mean, and non-parametric tests (Wilcoxon signed-ranked test and Kruskal wallis test) were used to determine whether there was a significant difference in FOXN3/ACTB mRNA expression. The chi square test was used to examine the relationship between protein expression and clinical parameters, a p value of < 0.05 is considered significant.
Results
Clinical and demographic characteristics of patients
Breast tumor and adjacent normal tissue of 142 breast cancer patients were collected at the time of surgery. The clinical and demographic data of the patients was gathered based on the questionnaire filled in by the patients and the clinical tests performed before or after the surgery. The mean age of menopause was calculated to be 44.65 ± 0.63 years in the patients included in the study (Table 1).
Table 1.
Clinicopathological parameters of the patients included in the study.
| Characteristics | Cases (%) |
|---|---|
| Tissue | |
| Normal | 142 (100) |
| Tumor | 142 (100) |
| Age (years) | |
| ≤ 50 | 80 (56.34) |
| > 50 | 62 (43.66) |
| Menopausal status | |
| Premenopausal | 55 (38.7) |
| Postmenopausal | 87 (61.3) |
| Age at menopause (years) | |
| ≤ 45 | 45 (51.72) |
| > 45 | 42 (48.28) |
| Estrogen receptor status | |
| Negative | 81 (57) |
| Positive | 61(43) |
| Progesterone receptor status | |
| Negative | 91 (64.1) |
| Positive | 51 (35.9) |
| Her2 neu status | |
| Negative | 89 (62.7) |
| Positive | 53 (37.3) |
| Lymph node status | |
| Negative | 39 (27.5) |
| Positive | 103 (72.5) |
| Tumor size (cm) | |
| ≤ 5 | 46 (32.4) |
| > 5 | 96 (67.6) |
| Histological grade | |
| (I + II) | 85 (59.9) |
| (III + IV) | 57 (40.1) |
| Clinical stage | |
| (I + II) | 41 (28.9) |
| (III + IV) | 101 (71.1) |
| Molecular subtype | |
| Luminal A | 39 (27.5) |
| Luminal B | 25 (17.6) |
| Her2 neu enriched | 28 (19.7) |
| TNBC | 50 (35.2) |
Differential expression of FOXN3 mRNA in breast tumor tissue vs. adjacent normal tissue
Real Time PCR results for FOXN3 mRNA expression analysis revealed its elevated expression in the breast tumor samples in comparison to adjacent normal tissue sample. ∆Ct method was used to compare the expression between tumor and control tissue by normalizing the expression of FOXN3 with ACTB gene. A mean fold change of 4.94 was calculated in the upregulated cases. Overall, 61.26% (87/142) cases had FOXN3 mRNA over expression and upon statistical analysis it was found to show significant association with menopausal status (p = 0.003) and lymph node status (p = 0.049) of the patients. (Table 2; Fig. 1)
Table 2.
FOXN3 mRNA expression and its correlation with clinicopathological parameters of the patients.
| Characteristics | Cases (%) | FOXN3 mRNA expression normalized with ACTB ± SE | p value |
|---|---|---|---|
| Normal | 142 (100) | 1.6855 ± 0.13755 | < 0.001* |
| Tumor | 142 (100) | 2.9449 ± 0.26626 | |
| Age (years) | |||
| ≤ 50 | 80 (56.3) | 2.9138 ± 0.40438 | 0.105 |
| > 50 | 62 (43.66) | 3.5626 ± 0.44528 | |
| Menopausal status | |||
| Premenopausal | 55 (38.7) | 2.0353 ± 0.41096 | 0.003* |
| Postmenopausal | 87 (61.3) | 3.9315 ± 0.39633 | |
| Age at menopause (years) | |||
| ≤ 45 | 45 (51.72) | 3.6440 ± 0.54741 | 0.385 |
| > 45 | 42 (48.28) | 4.2394 ± 0.57748 | |
| Estrogen receptor status | |||
| Negative | 81 (57) | 3.2312 ± 0.41083 | 0.744 |
| Positive | 61(43) | 3.1517 ± 0.43862 | |
| Progesterone receptor status | |||
| Negative | 91 (64.1) | 3.0307 ± 0.36124 | 0.859 |
| Positive | 51 (35.9) | 3.4938 ± 0.53220 | |
| Her2 neu status | |||
| Negative | 89 (62.7) | 2.9389 ± 0.35091 | 0.129 |
| Positive | 53 (37.3) | 3.6305 ± 0.54602 | |
| Lymph node status | |||
| Negative | 39 (27.5) | 2.1160 ± 0.38574 | 0.049* |
| Positive | 103 (72.5) | 3.6064 ± 0.37970 | |
| Tumor size (cm) | |||
| ≤ 5 | 46 (32.4) | 3.1704 ± 0.45331 | 0.806 |
| > 5 | 96 (67.6) | 3.2098 ± 0.38795 | |
| Histological grade | |||
| (I + II) | 85 (59.9) | 2.8798 ± 0.31513 | 0.248 |
| (III + IV) | 57 (40.1) | 3.6701 ± 0.57835 | |
| Clinical stage | |||
| (I + II) | 41 (28.9) | 3.0511 ± 0.47701 | 0.912 |
| (III + IV) | 101 (71.1) | 3.2563 ± 0.37544 | |
| Molecular subtype | |||
| Luminal A | 39 (27.5) | 3.0736 ± 0.56320 | 0.895 |
| Luminal B | 25 (17.6) | 3.2666 ± 0.68235 | |
| Her2 neu enriched | 28 (19.7) | 3.6863 ± 0.80706 | |
| TNBC | 50 (35.2) | 2.9846 ± 0.47229 | |
* and bold represents the significant value.
Fig. 1.
Box plots representing significant change in expression of FOXN3 mRNA (A) Breast tumor and adjacent normal tissue. (B) Pre-menopause and post-menopause cases (C) Lymph node negative and Lymph node positive cases.
Breast tumor tissues exhibited elevated expression of FOXN3 protein
To evaluate the expression of FOXN3 at the protein level, immunohistochemistry and western blot analyses were performed, revealing that 59.15% (84/142) of cases exhibited higher expression in breast tumor tissue. However, 40.85% (58/142) of cases showed weak immunoreactivity for the FOXN3 protein. The majority of the samples showed nuclear staining. Upon correlating FOXN3 overexpression with clinical parameters, a significant association was found with menopause status (p = 0.008), lymph node status (p = 0.001), and clinical stage of the patients (p = 0.018) (Table 3, Figs. 2 and 3).”
Table 3.
FOXN3 protein expression and its correlation with clinicopathological parameters of the patients.
| Characteristics | Cases (%) | Low FOXN3 (%) | High FOXN3 (%) | p value |
|---|---|---|---|---|
| Age (years) | ||||
| ≤ 50 | 80 (56.3) | 38 (26.76) | 42 (29.58) | 0.067 |
| > 50 | 62 (43.66) | 20 (14.08) | 42 (29.58) | |
| Menopausal status | ||||
| Premenopausal | 55 (38.7) | 30 (21.13) | 25 (17.61) | 0.008* |
| Postmenopausal | 87 (61.3) | 28 (19.72) | 59 (41.55) | |
| Age at menopause (years) | ||||
| ≤ 45 | 45 (51.72) | 16 (18.39) | 29 (33.34) | 0.486 |
| > 45 | 42 (48.28) | 12 (13.79) | 30 (34.48) | |
| Estrogen receptor status | ||||
| Negative | 81 (57) | 29 (20.42) | 52 (36.62) | 0.159 |
| Positive | 61(43) | 29 (20.42) | 32 (22.54) | |
| Progesterone receptor status | ||||
| Negative | 91 (64.1) | 36 (25.35) | 55 (38.73) | 0.677 |
| Positive | 51 (35.9) | 22 (15.49) | 29 (20.42) | |
| Her2 neu status | ||||
| Negative | 89 (62.7) | 36 (25.35) | 53 (37.32) | 0.901 |
| Positive | 53 (37.3) | 22 (15.49) | 31 (21.83) | |
| Lymph node status | ||||
| Negative | 39 (27.5) | 25 (17.61) | 14 (09.86) | 0.001* |
| Positive | 103 (72.5) | 33 (23.24) | 70 (49.30) | |
| Tumor size (cm) | ||||
| ≤ 5 | 46 (32.4) | 24 (16.90) | 22 (15.49) | 0.057 |
| > 5 | 96 (67.6) | 34 (23.94) | 62 (43.66) | |
| Histological grade | ||||
| (I + II) | 85 (59.9) | 38 (26.76) | 47 (33.10) | 0.253 |
| (III + IV) | 57 (40.1) | 10 (07.04) | 37 (26.05) | |
| Clinical stage | ||||
| (I + II) | 41 (28.9) | 23 (16.20) | 18 (12.68) | 0.018* |
| (III + IV) | 101 (71.1) | 35 (24.65) | 66 (46.49) | |
| Molecular subtype | ||||
| Luminal A | 39 (27.5) | 19 (13.38) | 20 (14.08) | 0.677 |
| Luminal B | 25 (17.6) | 10 (07.04) | 15 (10.56) | |
| Her2 neu enriched | 28 (19.7) | 11 (07.74) | 17 (11.97) | |
| TNBC | 50 (35.2) | 18 (12.68) | 32 (22.54) | |
* and bold represents the significant value.
Fig. 2.
Representative panel of immunohistochemical images for FOXN3 protein detection in breast tissue (A) normal breast tissue (B) breast cancer tissue showing low expression of FOXN3 protein (C) breast cancer tissue with high expression of FOXN3 protein.
Fig. 3.
FOXN3 protein expression analysis through western blot (A) elevated expression of FOXN3 in tumor tissue as compared to its paired normal breast tissue (B) comparative analysis of FOXN3 normalized with Beta actin expression in normal and breast tumor tissues (p < 0.001).
FOXN3 is not mutated in Indian breast cancer patients
The mutations in the DNA binding domain of FOXN3 gene were analyzed through automated DNA sequencing. We do not report mutation in these domains of FOXN3 gene (Fig. 4).
Fig. 4.
Representative image of agarose gel of PCR product and sequencing data (A) exon 2 (627 bp) (B) exon 3 (419 bp).
Reactome and GO analysis of DEGs
Differential gene expression analysis was performed for the breast cancer patient’s dataset and total of 1091 genes (495 downregulated and 596 upregulated) were identified. We constructed the relevant heat map (S3) and volcano plot in accordance with it (Fig. 5A). Further, gene set enrichment analysis was performed on the screened DEGs, and we found a significant correlation with immune system signaling. The FOXN3-related genes were then subjected to GO analysis, revealing a significant association with biological processes, including cellular response to cytokine stimulus, regulation of the ERK1 and ERK2 cascade, and regulation of cell migration, among the top associated processes. Based on the Cellular component and Molecular function analysis for breast cancer patient’s dataset, FOXN3 was also found to be associated with collagen containing extracellular matrix and calcium ion binding respectively (Fig. 5B).
Fig. 5.
(A) Volcano plot for the identified DEGs. (B i) Reactome pathway analysis for the DEGS and related genes in breast cancer dataset. (B ii–iv) GO analysis for the DEGS and related genes in breast cancer Biological Process, Molecular Function and Cellular Component respectively.
FOXN3 overexpression is associated with poor survival
The GEPIA2 tool is an online resource to explore the differential expression of genes and their clinical significance in cancer. We compared the survival of patients with higher expression of FOXN3 gene with low expression, patients with the higher expression were found to have poor survival (Fig. 6).
Fig. 6.
GEPIA2 analysis to compare survivalship of the patients with low FOXN3 and high FOXN3 expression.
Discussion
Even after rigorous research and advancement made in diagnosis and treatment, the steady rise in breast cancer incidence has compelled clinicians and researchers to revisit our traditional approaches in managing this disease22. The molecular subtype, stage and grade of the tumor are key decisive factors that are considered while preparing the strategy to combat the disease. Typically, during the course of treatment, resistance to systemic therapies is frequently reported and makes it more difficult to get efficient treatment23,24. Even though the majority of the patients share common histological features at the time of diagnosis, the underlying molecular aspects of the disease lead to varied clinical outcomes in response to traditional therapies25,26. To ensure more assertive clinical outcomes and survival of the patients, a personalized approach for treatment with a better understanding of molecular drivers of chief pathways involved in progression of breast cancer is needed27–29.
FOXN3 is a member of Forkhead box family of transcription factors that possess evolutionarily conserved DNA binding domain. FOXN3 is known to have a crucial role in various biological processes like cell cycle progression, gene regulation and maintenance of homeostasis. Hence, they have gained the attention of researchers to investigate their role in tumorigenesis in the past few decades6,7,30.
The expression study of FOXN3 gene in breast cancer cases was conducted at mRNA and protein level. We performed FOXN3 mRNA expression analysis through real time PCR, our data exhibited the upregulation of FOXN3 mRNA in 87 out of 142 breast cancer cases and mean fold change was calculated to be ~ 4.9 in the upregulated cases. Further, protein expression study via immunohistochemistry (IHC) and western blotting revealed the elevated expression of FOXN3 protein in 59% of cases with its prominent nuclear localization. Previous studies to evaluate the expression levels and molecular function of FOXN3 in cancer tissue revealed its enigmatic association with different cancers11,31,32. FOXN3 binds to the promoter region of E2F5, an oncogene in hepatocellular carcinoma and represses its expression11. In colon cancer cells, FOXN3 is reported to bind with beta-catenin and block its association with TCF433. Interestingly, in a recent study on pancreatic cancer cohort, an opposite role of FOXN3 was observed and it was found that overexpression of FOXN3 was positively associated with progression of the disease32. Similar function of FOXN3 is also reported in breast cancer cases and can possibly promote breast cancer development via NEAT1/SIN3A/FOXN3 axis in estrogen positive cells. In estrogen positive cells NEAT1 expression is induced by ER; NEAT1 is crucial for FOXN3 and SIN3A interaction and thereby forming NEAT1/FOXN3/SIN3A complex. The expression of estrogen induces NEAT1 which forms FOXN3-NEAT1-SIN3A complex that in turn transcriptionally represses the ERα expression thereby forming a negative feedback loop. Moreover, FOXN3 and NEAT1 were reported to be upregulated in breast cancer patients and their high expression was linked with poor survival of the patients14,15. The findings of our expression study on breast tumor tissue samples corroborated with the study conducted by Li et al. in 2017 and FOXN3 overexpression was observed at both mRNA and protein level.
Further, to evaluate the clinicopathological significance of FOXN3 expression in breast cancer patients, suitable statistical tests were performed considering p < 0.05 to be significant. Post-menopausal and lymph node positive cases exhibited a significant correlation with the elevated expression of both FOXN3 mRNA and protein. In females, late menopause increases their risk of developing breast, uterine and ovarian cancers34. Interestingly majority of females having menopause after age of 45 (30/42 cases) exhibited the higher expression of FOXN3, although the correlation was not found to be significant. The bioinformatics study on pancreatic cancer cases using oncomine database revealed the significant correlation of FOXN3 overexpression with the positive lymph node status of the breast cancer patients32. Our findings corroborated with the previously published literature, and we report significant association of lymph node positive status with the elevated expression of FOXN3 at both mRNA and protein level. These findings indicate a possible role of FOXN3 in invasion and metastasis of the disease. Moreover, higher levels of FOXN3 protein in breast cancer samples also exhibited significant correlation with the advanced clinical stage of the patients. To develop better insight into treating breast cancer, it is necessary to identify the factors involved in its progression. The association of FOXN3 overexpression reveals its significance in progression of the disease, especially in case of breast cancer.
To examine any genetic alterations, we investigated the single nucleotide polymorphism in the region encoding for the DNA binding domain of FOXN3. We did not find any mutation in this region of FOXN3 gene in Indian breast cancer patients. Moreover, to examine the functional significance of FOXN3 in cancer related pathways, we identified the disease-enriched pathways using the collected gene expression data from GEO dataset. Such analysis indicates the over representation of certain diseases or disorders that are associated with specific genes or protein group. The enrichment analysis revealed the close association of FOXN3 in cellular response to cytokine stimulus and immune modulation. Similar findings were earlier reported in pancreatic cancer cases32.
The elevated levels of various cytokines are documented in different cancers and are known for their prominent role in promoting tumor growth35,36. Moreover, to evaluate the significance of FOXN3 in survival of the breast cancer patients, bioinformatics analysis was performed using GEPIA2 database. Patients with higher expression of FOXN3 were seen to have poor survival rates as compared to the patients having lower FOXN3 expression. Our findings corroborated with earlier study in pancreatic cancer cohort where FOXN3 was found to be associated with poor survival of the patients32. The role of FOXN3 in prognosis and patient survival based on FOXN3 expression level can potentially lead to more personalized treatment strategies. Our study provides novel insights into the clinical significance of FOXN3 expression as potential biomarker in breast cancer especially in Indian population. Our molecular findings and their association with clinical characteristics of the patients provides valuable information regarding breast cancer biology in Indian patients, adding to population-specific knowledge and insights for future therapeutic and prognostic advancements. However, our study does not include the functional validation of role of FOXN3 in breast cancer or investigate its regulatory mechanisms. Further, studies to evaluate the molecular functions of FOXN3 gene can be helpful to enhance our understanding of its interactions and regulation in breast cancer cells. Also, a study on larger a population size and other ethnic groups would determine the connection of FOXN3 gene in breast cancer progression and its therapeutic targeting.
Conclusion
In conclusion, our study revealed the elevated expression of FOXN3 at both mRNA and protein level in Indian breast cancer patients. Earlier research exhibited the role of FOXN3 in ER + breast cancer cells where it was found to be member of NEAT1/SIN3A/FOXN3 axis, however, there has been no study emphasizing the connection of FOXN3 with clinical variables in breast cancer patients. The overexpression of FOXN3 gene in Indian breast cancer patients is first time reported in our study where post-menopausal females were found to have significant correlation with the higher expression of FOXN3 gene. Further studies on larger population would facilitate our understanding in determining the role of FOXN3 gene in breast cancer.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Acknowledgements
The authors are thankful to University Grant Commission (UGC), New Delhi, India, and the deanship of Research and Graduate Studies, King Khalid University for financially supporting to this study through Large Research Group Project under Grant no. R.G.P.2/153/46. The authors also acknowledge Core Diagnostics for immunohistochemistry analysis.
Author contributions
S.M. and S.A.H. wrote the main manuscript, S.A.H. and S.V.S.D. provided resourses, S.M., S.A.H. and M.A.K. designed the research, M.A.K., A.K., Z.M., and R.K. performed software analysis, S.M., M.H., S.M.H. and S.O.R. reviewed manuscript.
Funding
The author(s) received no specific funding for this work.
Data availability
The datasets generated and/or analyzed during the current study are available in the GenBank repository (PV204921 - PV205062; PV205063 - PV205204).
Declarations
Competing interests
The authors declare no competing interests.
Ethical approval and consent to participate
The Institute Ethics Committee, AIIMS, New Delhi (IEC-849/03.12.2021) and the Institutional Ethics Committee, JMI, New Delhi (25/7/236/JMI/IEC/2019) provided ethical permission for this research. Written consent was taken from the participants included in the study.
Footnotes
Publisher’s note
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Contributor Information
Sheersh Massey, Email: masseysheersh@gmail.com.
Syed Akhtar Husain, Email: shusain@jmi.ac.in.
References
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets generated and/or analyzed during the current study are available in the GenBank repository (PV204921 - PV205062; PV205063 - PV205204).