Transcriptomic Profiling Reveals the Underlying Mechanism of Interferon-Epsilon (IFN-ε) and Interferon-Gamma (IFN-γ) Combination in Cervical Cancer Volume 54- Issue 1

Jiaqi Zhang^1#, Yuxin Deng^1#, Yuewen Fang¹, Ming Xie¹, Jia Yu¹, Siew Woh Choo^1-4* and Xuechen Tian^1-4*

• ¹Department of Biology, College of Science, Mathematics and Technology, Wenzhou-Kean University, China
• ²Zhejiang Bioinformatics International Science and Technology Cooperation Center, Wenzhou-Kean University, China
• ³Wenzhou Municipal Key Lab for Applied Biomedical and Biopharmaceutical Informatics, Wenzhou-Kean University, China
• ⁴Dorothy and George Hennings College of Science, Mathematics and Technology, Kean University, USA
• ^#These authors are contributed work equally.

Received: December 06, 2023;   Published: December 21, 2023

*Corresponding author: Xuechen Tian, Wenzhou Municipal Key Lab for Applied Biomedical and Biopharmaceutical Informatics, 88 Daxue Road, Ouhai, Wenzhou, Zhejiang Province, 325060 China.
Siew Woh Choo, College of Science, Mathematics and Technology, Wenzhou-Kean University, 88 Daxue Road, Ouhai, Wenzhou, Zhejiang Province, 325060 China.

DOI: 10.26717/BJSTR.2023.54.008510

Abstract PDF

Cervical cancer remains a global health challenge, with its treatment necessitating novel therapeutic strategies. This study delves into the synergistic effects of interferons IFN-ε and IFN-γ on cervical cancer using high-throughput sequencing technology, specifically targeting the HaLa S3 cell line. Our cell viability assays demonstrate that the combination of IFN-ε and IFN-γ exerts a substantial inhibitory effect on these cells. Transcriptomic analysis revealed a total of 6,265 differentially expressed genes (DEGs) were identified in cells treated by IFN-ε and IFN-γ, including 3,363 significantly up-regulated DEGs and 2,902 significantly down-regulated DEGs. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses suggest that the up-regulated DEGs mainly enriched in immune response, inflammatory response, and signaling receptor binding activities, while down-regulated DEGs are mainly associated with the mitotic cell cycle, DNA replication, and cancer metabolism pathways. These results suggest that the antitumor properties of IFN-ε and IFN-γ combination are conferred through both an up-regulation of immune and inflammatory responses and a negative regulation of cell cycle and cancer metabolism. It can be achieved through direct modulation of cancer cells or indirectly through components of the immune system. This study provides new insights into the complex molecular interactions and signaling pathways regulated by a combination of type I and II interferons, which contribute to the development of advanced immunotherapeutic strategies in the fight against cervical cancer.

Keywords: Cervical Cancer; Interferon-Epsilon; Interferon-Gamma; Combination Drug; Anti-Cancer

Abbreviations: DEGs: Differentially Expressed Genes; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; HPV: Human Papillomavirus; WHO: World Health Organization; DMEM: Dulbecco Modified Eagle Medium; CC: Cellular Component; BP: Biological Process; TME: Tumor Microenvironment

Cervical cancer, primarily induced by persistent Human Papillomavirus (HPV) infection, is a critical public health concern and one of the most prevalent malignancies affecting women aged 15 to 44. The global burden of this disease is stark, with over 604,000 new cases and 340,000 deaths reported in 2020 (WHO [1]). The urgency of addressing cervical cancer is underscored by World Health Organization (WHO) projections, which estimate that with proper treatment for 90% of the cases, around 62 million deaths could be averted over the next century (Canfell, et al. [2]). However, the existing therapeutic interventions, particularly for early-stage cervical cancer, which include surgery and chemotherapy, either alone or in tandem, have been reported to achieve cure rates of only 50% to 60% (Hill [3]). Such statistics not only highlight the acute need for improved treatment options but also underscore the complexities associated with managing this disease. Patients with recurrent or metastatic cervical tumors face a grim prognosis, with few treatment alternatives at their disposal. These existing treatments are frequently associated with severe side effects and a poor quality of life, as reflected in the literature (Ferrall, et al. [4]). Consequently, the exploration and development of new pharmacological agents capable of reducing mortality and morbidity associated with cervical cancer are imperative. Interferons (IFNs), a family of glycoproteins, have long been recognized for their antiviral and immunomodulatory properties and have found widespread use in cancer therapy (Cheon [5,6]).

They play a pivotal role in the innate immune system’s response to cancerous cells. Notably, Interferon epsilon (IFN-ε) has demonstrated significant anti-cancer effects by promoting apoptosis and inhibiting the proliferation of cancer cells in earlier studies (Cao, et al. [7,8]). It also exhibits dynamic blood concentration changes at different stages of HPV infection and cervical cancer development (Li [9,10]). Furthermore, IFN-ε’s ability to curtail tumor growth by impeding angiogenesis has been documented (Ishida, et al. [11]). Interferon-gamma (IFN-γ), another cytokine, has exhibited anti-cancer effects with its antiproliferative, antiangiogenic, and proapoptotic properties, and has been considered for the treatment of various cancers, including melanoma and colon cancer (Mojic [12,13]). Despite the promising potential of both IFN-ε and IFN-γ as therapeutic agents against cancer, the literature reveals a conspicuous gap in the collective understanding of their combined effects and mechanisms when deployed against malignancy. This deficit in knowledge necessitates a thorough investigation into the synergistic effects of IFN-ε and IFN-γ, especially considering the complex and multifactorial nature of cervical cancer progression. In this study, we utilized the HeLa S3 cell line, a robust in vitro model for cervical cancer, to evaluate the efficacy of this cytokine combination.

In addition to assessing the direct anti-cancer effects, such as reduced cell viability, we sought to unravel the molecular underpinnings of these effects using high-throughput sequencing technology. We anticipated that this approach would reveal a complex network of gene expression changes, providing insights into the immune-mediated anti-cancer mechanisms of IFN-ε and IFN-γ. Our study contributes vital insights into the complex molecular interactions and signaling pathways that a combination of type I and II interferons can regulate, highlighting the potential of IFN-ε and IFN-γ as a combinatory therapeutic approach through their ability to modulate the immune response while concurrently targeting cancer cell viability. Such insights advance our understanding of cervical cancer’s molecular landscape and provide a foundation for novel immunotherapeutic strategies that could transform patient outcomes. As a steppingstone, our research encourages further investigations into combinatory cytokine therapies to improve cervical cancer prognosis.

Cell Culture and Drug Preparation

HeLa S3 cells were grown in Dulbecco Modified Eagle Medium (DMEM) complete medium (Cytiva HyClone™, USA) consisting of 10% fetal bovine serum (FBS, Gibco™) and 1X penicillin-streptomycin (Cytiva HyClone™, USA). A 37 °C incubator containing 5% CO₂ atmosphere was used for cell culture. Cells were harvested for subsequent experiments once they reached 90% confluence. The recombinant human IFN-ε (9667-ME-025/CF, R&D System, USA) and IFN-γ (285- IF-100/CF, R&D System, USA) were purchased from the Bio-Techne company (Bio-Techne, USA), and IFN-ε was dissolved to 250 μg/ml stock in sterile ultrapure water, and IFN-γ was dissolved to 200 μg/ ml stock in sterile ultrapure water according to manufacturer’s specification.

Cell Viability Assay

Based on the earlier study (Choo[28]), the effective concentration of IFN-ε for HeLa S3 cancer cells is close to 800ng/ml, and the optimizing concentration of IFN-γ is 20ng/ml. HeLa S3 cells were seeded on 96-well plates with a density of 2x103 cells per well and incubated at 37℃ incubators containing 5% CO₂, after 24h, cells were treated with 800ng/ml IFN-ε alone, 20ng/ml IFN-γ alone, and a combination of 800ng/ml IFN-ε and 20ng/ml IFN-γ for 24h, 48h, 72h, and 96h. The microplate analyzer and Wst-1 Cell Proliferation and Cytotoxicity Assay Kit (Beyotime, China) were used to detect the cell viability and find the optimizing drug treatment time. Cell status and morphology were inspected under the inverted fluorescence microscope (Nikon, Japan).

RNA Extraction and Integrity Analysis

HeLa S3 cells were cultured in 60 mm cell culture dishes at a density of 2 × 10⁴ cells/ml for 24h. After removing the old medium, cells were washed twice with PBS (Cytiva HyClone™, USA), and 3 ml of fresh complete medium was precisely added to each dish. Cells were treated with 800 ng/ml of IFN-ε and 20 ng/ml of IFN-γ for 72 hours, with the same volume of sterile water added to the control group. RNA of each sample was isolated from cells using TRIzol reagent (Invitrogen, CA) following the manufacturer’s protocol. The concentration and purity of the total RNA of each sample were inspected on a spectrophotometer (NanoDrop 2000, Thermo Fisher Scientific Inc.), and total RNA integrity was evaluated using the Agilent 2200 Bioanalyzer (Agilent Technologies, USA).

Library Construction and Transcriptome Sequencing

RNA library preparation and sequencing were performed using Illumina sequencing technology. The NEBNext Poly(A) mRNA Magnetic Isolation Module was utilized to isolate poly(A) mRNA and generate mRNA fragments. The synthesis of first-strand cDNA was performed using the ProtoScript II reverse transcriptase, first-strand synthesis reaction buffer, and random primers. The second-strand cDNA was generated using Enzyme mix. The purified double-stranded cDNA fragments were repaired at both ends, followed by dA-tailing and adaptor ligation. Size selection of Adaptor-ligated DNA was then performed using DNA Clean Beads. PCR amplification was carried out for each sample using P5 and P7 primers and PCR products were validated using a Qsep100 (Bioptic, Taiwan, China), and quantified by Qubit3.0 Fluorometer (Invitrogen, Carlsbad, CA, USA). The libraries were loaded on an Illumina Novaseq 6000 instrument and sequenced using a 2×150 paired-end configuration according to the manufacturer’s instructions (Illumina, San Diego, CA, USA). Image analysis and base calling were performed using Bcl2fastq (v2.17.1.14).

Quality Control and Alignment

All raw sequences generated by RNA sequencing were obtained in fastq format. Adapters, low-quality bases (Q<20), or N-containing bases were removed by Cutadapt (V1.9.1). The clean reads were aligned with the human reference genome (GRCh38 download from Ensembl) using Hisat2 (V2.0.1).

Differential Gene Expression Analysis

The gene expression levels of each sample were estimated by Fragments Per Kilobase of transcript per Million mapped reads (FPKM) using Htseq software (V0.6.1). To identify differentially expressed genes (DEGs), the DESeq2 Bioconductor package (V1.26.0) was used for the comparison between controls and treated samples. FDR-adjusted P-value ≤ 0.05 and |log2(fold change) |≥1 was set as the cut-off criteria for detecting up-regulated and down-regulated genes. Gene Ontology (GO) and KEGG Pathway Enrichment Analysis Web-based Gene Set Analysis Toolkit (https://www.webgestalt. org/) was utilized to perform GO and pathway enrichment analysis. The DEGs identified were mapped to corresponding GO terms categorized with respect to cellular component (CC), molecular function (MF), and biological process (BP). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out for both the up-regulated and down-regulated genes to identify the significantly enriched pathways. A False Discovery Rate (FDR) <0.05 was considered significant.

Data Statistics

All results were expressed as Mean± SEM in the graphs. For each assay, there were more than three independent biological replicates. We used an unpaired t-test to analyze whether there was a significant difference between the control group and the treatment group. When the P-value of the unpaired t-test is smaller than 0.05, the result is considered statistically significant. GraphPad Prism (version 9.0) (GraphPad Software, San Diego, California USA, www.graphpad.com) was used in statistical analysis.

The Combined IFN-ε and IFN-γ Exhibit Anticancer Activity in HeLa S3 cells

To evaluate the optimal treatment duration using combination drugs (IFN-ε and IFN-γ), we performed a cell viability assay. Figure 1A presents the results of this time optimization. After 24 hours of treatment, we observed an inhibitory rate of approximately 10%. This rate increased to about 20% at 48 hours and approximately 50% at 72 hours. Notably, after 96 hours, cell viability dropped to below 40%. Given these findings and experimental considerations, we selected the 72-hour treatment duration for subsequent experiments. Furthermore, as illustrated in Figure 1B, the combination of IFN-ε and IFN-γ exhibited a greater inhibitory effect than either IFN-ε or IFN-γ alone after 72 hours. This underscores the potency of the combined treatment in reducing the viability of HeLa S3 cells. Morphological observations highlighted distinct changes in cell morphology and cell count between the control and treated groups (Figure 1C). These findings collectively indicate that the combination of IFN-ε and IFN-γ enhances the suppression of HeLa S3 cells and induces notable morphological alterations compared to solo treatments.

Figure 1

Quality Control of RNA Samples

To further explore the underlying mechanism of IFN-ε and IFN-γ on human cervical cancer, we performed transcriptome sequencing by comparing the control (untreated) with the IFN-ε and IFN-γ treated samples (treatment). Four biological replicates were used for each group. After sequencing, a total number of 291,585,252 and 288,560,724 raw reads of 150 bp were generated from the controls (C1, C2, C3, C4) and IFN-treatment groups (EG1, EG2, EG3, EG4), respectively (Supplementary Table 1). After being trimmed for adapters and low-quality bases, 290,709,262 and 287,835,478 clean reads were obtained from the control and treatment groups. The total bases of the clean data were about 85 GB, and all groups had a Q30 percentage over 90% (Table 1).

Supplementary Table 1: Summary of the raw reads.

Table 1: Summary of the clean reads after filtering.

Note: C: control groups, EG: groups treated with IFN-ε and IFN-γ.

Transcriptome Analysis

As shown in Table 2, the overall mapping ratio of the clean read’s ranges from 88% to 92%. For each sample, at least 81% of the reads were uniquely mapped to the GRCh38 human reference genome. The above results show a satisfactory level of quality in the read alignment. Additionally, the expression profiles of all genes in the eight samples were normalized by the FPKM method and visualized using a boxplot (Figure 2). After normalization, the expression distributions of all samples were at a similar level, indicating that the normalization is successfully and the samples are suitable for comparisons.

Table 2: Mapping statistics of the clean reads to the reference genome.

The main constituents of N. sativa seeds (Figure 4) are fixed oil, proteins, carbohydrates, crude fiber, minerals, and essential oil. Detailed compounds of these constituents are listed in (Table 2). Other new compounds include the triterpene saponin (3-O-[-D-xylopyranosyl-( 1 2)--Lrhamnopyranosyl-(1 2)--Dglucopyranosyl]The steroidal glucoside (stigma-5,22-dien-3--D-glucopyranoside), the cycloartenol (3-O-[-D-xylopyranosyl-(1 3)--L-rhamnopyranosyl-(1 4)--D-glucopyranosyl]nigellidine-4-O-sulfite, as well as -11-methoxy- 16-hydroxy-17-acetoxy hederagenin were detected in the chemical composition of N. sativa [32,33]. Magnoflorine, kaempferol 3-O-rutinoside, and -hederin are among the new ingredients recently discovered [34]. Added to the above, many micronutrients and fatty acids (linoleic, oleic, and palmitic acids) also found within the plant contents [35]. Seven monoterpene hydrocarbons in N. sativa made up 52.61% of the overall composition of essential oil; p-cymene (28.76%), -thujene (12.88%), trans-verbenol (5.99%), -pinene (3.71%), -pinene (3.69%), sabinene (1.7%), and limonene (1.69%). The oxygenated monoterpene group in N. sativa essential oils was dominated by 2-isopropyl-5-methyl-1,4-benzoquinone (35.7%), also known as thymoquinone. There are five components in N. sativa hydrosol; 1,8-cineole (0.4%), linalool (0.5%), trans-verbenol (2.83%), terpinen-4-ol (7.21%), and thymoquinone (89.05%) [36]. LC-MS/MS analysis of the N. sativa cake revealed 36 distinct chemicals [37].

The investigations found that N. sativa seedcake contains a variety of phytochemicals, including a high quantity of protein, carbs, fiber, alkaloids and flavonoids, and phenolics with strong antioxidant activity [35]. The hydroethanolic N. sativa extract caused collagen fibers to be well ordered and epidermal diameter to grow significantly [38]. The analysis of detected phytocompounds from the GC-MS spectrum revealed that they had high reacting affinity for wound healing-associated target proteins including PKC-II, TNF, IL-1, PDGFRA, VEGF-A, and TGFBR1 kinase [39].

Figure 4

Table 2: N. sativa seed main phytochemicals.

Figure 2

Differential Gene Expression Analysis

Compared with the control group, a total of 6,265 differential expressed genes (DEGs) were identified in cervical cancer cells treated with a combination of IFN-ε and IFN-γ, among which 3,363 (53.7%) genes were up-regulated, and 2,902 (46.3%) genes were down-regulated (Figure 3). Detailed information on the top 10 up-regulated and down-regulated genes based on fold change is shown in Table 3 below. For the full list of DEGs, please refer to the supplementary information (Supplementary Tables 2 & 3).

Figure 3

Table 3: The top 10 up-regulated and down-regulated DEGs.

Supplementary Table 2: List of the up-regulated DEGs. Click here for Supplementary Table 2

Supplementary Table 3: List of the down-regulated DEGs. Click here for Supplementary Table 3

Gene Ontology (GO) and KEGG Pathway Enrichment Analysis

To get better insights into the functions of the DEGs, we performed GO and KEGG pathway enrichment analyses. Our GO analysis of the upregulated DEGs showed that they were enriched in biological processes related to immune responses (389 genes) and were enriched in the inflammatory response (184 genes). The innate immune response, defense response, and immune effector process were among the most up-regulated GO categories, confirming the immune stimulation effects of IFN-ε and IFN-γ on cervical cancer cells (Figure 4A). In comparison, the down-regulated genes were mostly enriched in biological processes related to the mitotic cell cycle, chromosome organization, DNA repair, and replication, implying that the treatment of combined interferons has an inhibitive effect on the malignant proliferation of cervical cancer cells (Figure 4B). For cellular components, the up-regulated genes were enriched in the plasma membrane, including the endoplasmic reticulum, Golgi apparatus, organelle sub-compartment, vesicle, and cell surface. Meanwhile, the downregulated DEGs were mainly enriched in the cytoskeleton, mitochondrion, envelope, and chromosome. The locations of DEGs were consistent with the biological functions mentioned above. Regarding molecular functions, the up-regulated genes were mainly enriched in molecular function regulator, identical protein binding, regulatory region DNA binding, and receptor activity, participating in the signal transduction mediated by cytokines.

The downregulated DEGs were enriched in nucleotide binding, ribonucleotide binding, ATP binding, and cytoskeletal protein binding. Additionally, KEGG pathways analysis results of the up-regulated DEGs reveal the activation of multiple pathways associated with immune responses, including Staphylococcus aureus infection (29 genes), graft-versus-host disease (21 genes), Type I diabetes mellitus (21 genes), allograft rejection (18 genes) and viral infection-related pathways such as viral myocarditis, Influenza A, Epstein-Barr virus infection, Herpes simplex infection, Hepatitis C, and Human papilloma virus infection (Figure 5A). KEGG pathways of the downregulated DEGs are mostly related to cell cycle and cancer metabolism (Figure 5B). Twenty-five up-regulated DEGs were reported in the DNA replication pathway, and 18 up-regulated DEGs were enriched in the base excision repair pathway. Ten up-regulated DEGs were found in the steroid biosynthesis pathway. Detailed results of the KEGG analysis are shown in Figure 5 below.

Figure 5

In this study, a more potent anti-cancer effect was discovered in the group treated with IFN-ε and IFN-γ combination than in the IFN-ε alone group and IFN-γ alone group. This combination could reduce viability and inhibit the proliferation of HeLa S3 cells. The IFN-ε and IFN-γ combination could also have significant morphological changes observed in HeLa S3 cells after 72h treatment. The combination of IFN-ε and IFN-γ might be a possible medication for cervical cancer based on in vitro results. It was worth carrying out future in vivo tests and developing a new therapy for cervical cancer. This result pointed out that the combination of two interferons could have more potent effects than a single interferon alone. The following research directions might exit more potential therapies by combining different interferons and other chemicals. Additionally, the IFN-ε and IFN-γ combination might not only function on cervical cancer but also inhibit the development of other cancers, which deserves more studies in the future. Furthermore, we present the first study to explore the underlying mechanism of the combined IFN-ε and IFN-γ in the cervical cancer cell line. We reported the identification of 6,265 DEGs in cancer cells treated with IFNs, including 3,363 up-regulated DEGs and 2,902 down-regulated DEGs. HLA-DRA, HLA-DRB1, and HLA-DQA1 were among the top up-regulated DEGs, which encode for major histocompatibility complex (MHC) class II proteins.

Consistent with our observations, the expression of MHC II molecules has been positively associated with levels of IFN-γ through cell-type-specific CIITA gene transcription and the regulation of tumor-infiltrating lymphocytes (Axelrod [14]). In cervical adenocarcinoma, up-regulated HLA-DRA expression has been related to increased disease-free and disease-specific survival (Samuels, et al. [15]). It implies that HLA-DRA may represent a potential biomarker for predicting patients’ response to immunotherapies but its exact role in cervical cancer needs further analysis due to the presence of contradictory results. Meanwhile, GBP1P1, GBP1, GBP5, and GBP4 from the Guanylate-binding proteins (GBPs) gene family were also significantly up-regulated. Previous research from Zhao, et al. [16] has reported a positive correlation between the expression level of GBP1 and immune cell infiltration in multiple tumor tissues. It implies that GBPs may play an important role in interferon-mediated antitumor immune responses in cervical cancer. Down-regulated DEGs represented by CA9, MAPK4, and AGR2 were mainly associated with the proliferation, differentiation, and migration of malignant cells (Guan, et al. [17-19]). Therefore, the combined IFN-ε and IFN-γ treatment may inhibit the growth of the cervical cells by inhibiting the proliferation, differentiation, and migration of the malignant cells. GO and KEGG pathway enrichment analysis suggests that the up-regulated DEGs were mainly enriched in pathways related to immune and inflammatory responses.

Most of the DEGs are located on the cell surface and the plasma membrane, which is reasonable since the phosphorylation and activation of STATs at the plasm membrane is central to many of the biological processes mediated by IFNs (Platanias [20]). As expected, the classic JAK/STAT pathway and cytokine-cytokines receptor interactions were up-regulated in response to the combined IFN treatment. Additionally, the antigen processing and presentation process was among the most enriched pathways, with 15 genes encoding for MHC class I and class II molecules significantly upregulated. Previous research has associated type I IFNs and IFN-γ exposure with antitumor M1 macrophage maturation and enhanced antigen presentation and migratory capabilities of dendritic cells inside the tumor microenvironment (TME) (Fenton [21]). Alternatively, IFNs have also been shown to induce MHC I expression in cancer cells, leading to increased antigenicity (Lorenzi, et al. [22]). It implies that antitumor functions of IFN-ε and IFN-γ may be achieved through the induction of immunity-related pathways or direct modulation of cancer cells. Interestingly, our data showed that many viral infection-related pathways including the human papillomavirus infection pathway were induced after the combined interferon treatment. This is consistent with the fact that interferons are known to exhibit antiviral activity (Samuel [23]). Moreover, HeLa cells have been shown to contain multiple human papillomavirus 18 (HPV-18) gene integration sites (Yu, et al. [24]).

The antiviral activity of the interferons may be important to inhibit or kill the HPV-18 in the cervical cell line. In other words, our combined interferon treatment is able to inhibit both HeLa S3 cancer cell growth and the virus since they have both anticancer and antiviral activities. The downregulated DEGs were mainly enriched in GO categories and KEGG pathways associated with the mitotic cell cycle, DNA replication, and cancer metabolism. A cluster of MCM genes, including MCM 2, 3, 4, 5, 6, and 7 were significantly downregulated in the DNA replication pathway. Elevated expression of minichromosome maintenance proteins (MCMs) has been observed in various malignancies, which contributes to tumor progression through the regulation of cell cycles (Wang, et al. [25]). Wu [26] reported a positive correlation between MCMs expression and the proliferation and differentiation of cervical cancer cells. It suggests that the combined IFN-ε and IFN-γ treatment may play an important role in suppressing the replication of cervical cancer cells. Additionally, our analysis suggests the combined IFN treatment also led to a decrease in carbon metabolism and the biosynthesis of amino acids and steroids which fuel and support cancer cell proliferation. Recent studies suggest steroidogenesis mediated by type 2 T cells contributes to the formation of immunosuppressive TME (Mahata, et al. [27]). Inhibition of the corresponding pathway increases functional T cells, M1 macrophages and reduces M2 macrophages, providing an alternative approach for the development of cancer immunotherapies.

Overall, this study explored the underlying mechanisms of IFN-ε and IFN-γ combination in cervical cancer. The results suggest that the antitumor properties of IFN-ε and IFN-γ combination are conferred through both an up-regulation of immune and inflammatory responses and a negative regulation of cell cycle and cancer metabolism. It can be achieved through direct modulation of cancer cells or indirectly through components of the immune system. These results provide new insights into the complex molecular interactions and signaling pathways regulated by a combination of type I and II interferons, which may also contribute to the development of cancer immunotherapies.

Another trial found that N. sativa oil was more effective as an antipsoriatic agent, particularly when taken as both a cream and a pill [43]. This confirmed that N. sativa possesses antipsoriatic properties and can alleviate psoriasis symptoms. One of the skin problems that N. sativa oil can help with is vitiligo, which is a condition that causes loss of skin color in patches. Vitiligo can affect the self-esteem and mental health of many patients. Some studies have explored the potential of N. sativa oil for treating vitiligo. A mixture of N. sativa oil and fish oil were tested on patients with vitiligo lesions. It has been found that both oils reduced the size of the lesions and improved the skin color [44]. Furthermore, when lizard skin used as a model, N. sativa oil increased the amount of melanin, which is the pigment that gives color to the skin. This explained that N. sativa oil enhanced the sensitivity of the receptors that control the production of melanin. Thymoquinone is the active ingredient N. sativa oil proposed to reduce external skin problems such as vitiligo and hypopigmentation [45].

X.T. and S.W.C. conceived this project. X.T., J.Z. and Y.D. contributed to the experiment design. Y.D., Y.F., M.X., J.Y. and J.Z. performed cell culture, cell viability assay, cell morphology examination. J.Z. and X.T. extracted RNA and performed RNA-sequencing data analysis. J.Z., Y.D., X.T., and S.W.C contributed figures, tables and interpretations. J.Z. and X.T performed most data analyses. J.Z. and X.T. wrote the manuscript. All authors proofread and approved the manuscript.

We would like to thank Professor Ferdinand Kappes from the Department of Life Sciences, Xi’an Jiaotong-Liverpool University, for his generosity in providing the HeLa S3 cell line for this study. We greatly thank the Laboratory and Research Center of Wenzhou-Kean University for providing excellent experimental resources for this study.

This work was funded by the Wenzhou-Kean University Student Partnering with Faculty/Staff Research Program (SpS2021030) and Bachelor’s program funding from the Office of Academic Affairs at Wenzhou University, as well as the high-level talent recruitment programme for academic and research platform construction (Reference Number: 5000105) from Wenzhou-Kean University.

No conflict of interest was declared.

The RNA sequencing data can be accessed at the National Center for Biotechnology Information (NCBI) Database (https://www. ncbi.nlm.nih.gov/) with the accession number for control group (SRX22856178, SRX22856179, SRX22856182, SRX22856183) and treatment group (SRX22856184, SRX22856185, SRX22856186, SRX22856187) in the article.

1. (2023) WHO Cervical cancer.
2. Karen Canfell, Jane J Kim, Marc Brisson, Adam Keane, Kate T Simms, et al. (2020) Mortality impact of achieving WHO cervical cancer elimination targets: a comparative modelling analysis in 78 low-income and lower-middle-income countries. Lancet 395: 591-603.
3. Hill EK (2020) Updates in Cervical Cancer Treatment. Clinical Obstetrics and Gynecology 63: 3-11.
4. Ferrall l, Lin KY, Roden RBS, Hung CF, Wu TC, et al. (2021) Cervical Cancer Immunotherapy: Facts and Hopes. Clinical Cancer Research 27: 4953-4973.
5. Cheon H, Borden EC, Stark GR (2014) Interferons and their stimulated genes in the tumor microenvironment. Seminars in oncology, Elsevier 41(2): 156-173.
6. Lin FC, Young HA (2014) Interferons: Success in anti-viral immunotherapy. Cytokine Growth Factor Rev 25: 369-376.
7. Cao X, Liang Y, Hu Z, LI H, Yang J, et al. (2021) Next generation of tumor-activating type I IFN enhances anti-tumor immune responses to overcome therapy resistance. Nature Communications 12: 5866.
8. Elorbany S, Malacrida B, Balkwill F (2023) Interferon epsilon and ovarian cancer. Trends in Cancer 9: 985-986.
9. Li H, Chen Y (2016) Expression and Clinical Significance of Interferon Epsilon in Peripheral in Patients with Cervical Cancer. Labeled Immunoassays and Clinical Medicine 23: 300-302.
10. Daniel Marrero R, Victor Baeza X, Keiko Taniguchi P, Victor Huerta P, Gustavo Ponce-Navarrete, et al. (2018) Interferon epsilon mRNA expression could represent a potential molecular marker in cervical cancer. International Journal of Clinical and Experimental Pathology 11: 1979.
11. Yuko Ishida, Toshikazu Kondo, Tatsunori Takayasu, Yoichiro Iwakura, Naofumi Mukaida, et al. (2004) The essential involvement of cross-talk between IFN-γ and TGF-β in the skin wound-healing process. The Journal of Immunology 172(3): 1848-1855.
12. Mojic M, Takeda K, Hayakawa Y (2017) The dark side of IFN-γ: its role in promoting cancer immunoevasion. International journal of molecular sciences 19: 89.
13. Zaidi MR (2019) The interferon-gamma paradox in cancer. Journal of Interferon & Cytokine Research 39(1): 30-38.
14. Axelrod ML, Cook RS, Johnson DB, Balko JM (2019) Biological consequences of MHC-II expression by tumor cells in cancer. Clinical cancer research 25(8): 2392-2402.
15. Samuels S, Spaans VM, Osse M, Peters LA, Kenter GG, et al. (2016) Human leukocyte antigen-DR expression is significantly related to an increased disease-free and disease-specific survival in patients with cervical adenocarcinoma. International Journal of Gynecologic Cancer 26(8): 1503-1509.
16. Zhao Y, Wu J, Li L, Zhang H, Zhang H, et al. (2022) Guanylate-binding protein 1 as a potential predictor of immunotherapy: a pan-cancer analysis. Frontiers in Genetics 13: 820135.
17. Chenyu Guan, Daiqiao Ouyang, Yongjie Qiao, Kan Li, Guangsen Zheng, et al. (2020) CA9 transcriptional expression determines prognosis and tumour grade in tongue squamous cell carcinoma patients. Journal of cellular and molecular medicine 24(10): 5832-5841.
18. Lee HJ, Hong CY, Kim MH, Lee YK, Nguyen-Pham TN, et al. (2012) In vitro induction of anterior gradient-2-specific cytotoxic T lymphocytes by dendritic cells transduced with recombinant adenoviruses as a potential therapy for colorectal cancer. Experimental & Molecular Medicine 44: 60-67.
19. Wang W, Shen T, Dong B, Creighton CJ, Meng Y, et al. (2019) MAPK4 overexpression promotes tumor progression via noncanonical activation of AKT/mTOR signaling. The Journal of clinical investigation 129(3): 1015-1029.
20. Platanias LC (2005) Mechanisms of type-I-and type-II-interferon-mediated signalling. Nature Reviews Immunology 5: 375-386.
21. Fenton SE, Saleiro D, Platanias LC (2021) Type I and II interferons in the anti-tumor immune response. Cancers 13(5): 1037.
22. Lorenzi S, Forloni M, Cifaldi L, Antonucci C, Citti A, et al. (2012) IRF1 and NF-kB restore MHC class I-restricted tumor antigen processing and presentation to cytotoxic T cells in aggressive neuroblastoma. PloS one 7(10):
23. Samuel CE (2001) Antiviral actions of interferons. Clinical microbiology reviews 14: 778-809.
24. Yu L, Lobanov A, Majerciak v, Mirza S, Band V, et al. (2020) Expression of HPV oncogenes from a single integration site in cervical cancer cell lines. bioRxiv 25: 171959.
25. Wang Y, Chen H, Zhang J, Cheng AS, Yu J, et al. (2020) MCM family in gastrointestinal cancer and other malignancies: from functional characterization to clinical implication. Biochimica et Biophysica Acta (BBA)-Reviews on Cancer 1874(2): 188415.
26. Wu B, Xi S (2021) Bioinformatics analysis of the transcriptional expression of minichromosome maintenance proteins as potential indicators of survival in patients with cervical cancer. BMC cancer 21(1): 1-17.
27. Mahata B, Pramanik J, Van Der Weyden L, Polanski K, Kar G, et al. (2020) Tumors induce de novo steroid biosynthesis in T cells to evade immunity. Nature communications 11: 3588.