Decoding the Relationships Among miRNA, HPV Infection, and Tumor Suppressor Gene Expression in Breast Cancer Patients

Decoding the Relationships Among miRNA, HPV Infection, and Tumor Suppressor Gene Expression in Breast Cancer Patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Decoding the Relationships Among miRNA, HPV Infection, and Tumor Suppressor Gene Expression in Breast Cancer Patients Zana Naderi, Malihe Hamidzade, Amir Hossein Yari, Hanieh Safarzadeh, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7269105/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted 19 You are reading this latest preprint version Abstract Breast cancer (BC) is one of the main causes of cancer-related deaths among women, with its incidence rising due to various risk factors (RFs), including viral infections such as Human Papillomavirus (HPV). This study investigates the correlation between HPV infection and the expression levels of key cellular genes, TP53, PTEN, and CCND1, as well as specific microRNAs (miR-106b-5p, miR-17-5p, and miR-20a-5p) in 102 breast cancer patients and 41 healthy controls. Results indicated a higher prevalence of HPV in BC samples; however, the difference in prevalence between BC and control groups was not statistically significant. ​Importantly, TP53 and CCND1 were significantly overexpressed in BC, while PTEN was downregulated.​ The expression levels of CCND1 in HPV-positive BC group was also increased. Further analysis revealed that miR-106b-5p and miR-20a-5p were expressed at elevated levels in HPV-positive BC patients in comparison to their HPV-negative counterparts. All of considered miRNAs were overexpressed in BC group. By using receiver operating characteristic (ROC) analysis, CCND1, plus TP53 and miR-20a-5p emerged as biomarkers for breast cancer diagnosis and differentiation of HPV status respectively. A weak negative correlation between PTEN and three miRNAs, and weak positive correlations between CCND1 and miR-106b-5p and also TP53 and miR-20a-5p were observed. These findings emphasize the potential role of HPV and related biomarkers in the progression of breast cancer, indicating avenues for further research and therapeutic strategies. Health sciences/Biomarkers Biological sciences/Cancer Biological sciences/Molecular biology Health sciences/Oncology Breast cancer HPV MicroRNA Gene expression Biomarkers Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Breast cancer (BC) is one of the most important causes of cancer related deaths among women worldwide [ 1 ]. The occurrence of breast cancer in women has exceeded that of lung, colorectal, prostate, and stomach cancers. Additionally, its incidence has risen due to the growing number of associated risk factors (RFs) [ 1 – 3 ]. Among RFs, infectious agents especially noroviruses could be involved as carcinogens or inducers [ 4 – 9 ]. Numerous studies have explored the impact of viral infections on the development of breast cancer, with HPV being identified as a significant risk factor. This highlights a meaningful connection between the presence of HPV and the occurrence of breast cancer [ 2 , 10 – 12 ]. The involvement of HPV in breast cancer was assessed by Lonardo et al. for the first time in 1992 [ 13 ]. Human Papillomavirus (HPV) is a non-enveloped virus belonging to Papillomaviridae family with circular double-stranded DNA as the genome [ 14 ]. HPV is known to be responsible for causing warts and certain types of cancer, as its involvement in these conditions has been clearly affirmed [ 14 ]. In numerous cases of HPV infections, the infection may be resolved on its own within two years. However, in some instances, the infection can persist and lead to precancerous changes and even cancer [ 15 , 16 ]. More than 170 types of HPV have been detected and about 40 types of them are involved in urogenital tract infections and also some types are associated with breast cancer [ 17 – 19 ]. HPV gene products/proteins have the crucial role in tumor development. E6 and E7 oncoproteins are the key factors involved in the virus's ability to cause cancer [ 20 , 21 ]. Both E6 and E7 can stimulate tumor development through interactions with p53, retinoblastoma (RB) and Bcl-2 [ 22 – 24 ]. Phosphatase and Tensin Homolog (PTEN) is an enzyme which acts as a tumor suppressor and can be found in almost all human tissues [ 25 , 26 ]. PTEN negatively regulates PI3K pathway which plays a critical role in the development and progression of different types of cancer [ 27 ]. It has been shown that E6 and E7 proteins can cause downregulation of the PTEN expression in lung cancer cells [ 28 ]. TP53, which encodes the p53 protein, is also recognized as a tumor suppressor gene. Together with PTEN, it plays essential roles in various biological processes like DNA repair, apoptosis, cell growth, and the progression of the cell cycle. Any dysfunction in these genes or changes in their expression can lead to unchecked tumor cell growth, allowing them to evade signals that normally halt cell division and trigger cell death [ 29 , 30 ]. CCND1, located on the long arm (q) of chromosome 11 at 11q13.3, encodes the Cyclin D1 protein, which is essential for transitioning from the G1 phase to the S phase of the cell cycle [ 31 , 32 ]. Additionally, its activity is positively regulated by the Retinoblastoma (RB) protein [ 33 , 34 ]. Previous studies have investigated the link between HPV infection and the expression levels of CCND1, revealing that HPV causes a decrease in CCND1 expression [ 35 , 36 ]. microRNAs (miR or miRNA) are a class of highly conserved small (about 22 nucleotides) single strand non-coding RNA molecules. Their function is based on being complementary to a part of one or more mRNAs. In animals, miRNAs typically attach to a site in the 3'-UTR of mRNAs, which results in the suppression of translation or the degradation of these mRNAs [ 37 , 38 ]. Research indicates that miRNAs play a role in around 60% of gene expression in human cells [ 38 – 40 ]. miRNAs influence viral infections and tumor progression in two primary ways, as outlined below: i) Directly: by targeting 3’-UTR (untranslated region) of viral oncogene mRNAs; ii) Indirectly: by targeting host cell mRNAs that are connected to normal cellular functions and/or the inhibition or progression of tumors [ 22 , 40 – 43 ]. miR-106b-5p has an important role in BC development [ 44 ]. miRNAs may play a role as a regulator of PTEN, as studies have shown that an increase in miR-106b-5p is linked to a decrease in PTEN levels in breast cancer. Additionally, it is also involved in suppressing apoptosis pathways [ 45 ]. miR-106b-5p overexpression contributes to cell invasion and is associated with 5-fluorouracil resistance in colorectal cancer patients [ 42 ]. miR-17-5p has been proposed as an anti-HIV factor in some researches, as well as oncomiR in BC in some other studies [ 46 – 48 ]. miR-20a-5p is an important miRNA which act as anticancer in some prevalent cancers such as BC. This miRNA is a possible breakthrough for the treatment of these cancers [ 49 ]. Cellular miRNAs can influence the levels of expression of some genes such as TP53, PTEN, and CCND1. Moreover, miRNAs also play a role in the expression of viral oncogenes. Taking these factors into account, examining the relationship between viral gene expression, cellular miRNAs, and cellular genes could enhance our understanding of how BC develops. In this study, the expression level of miR-106b-5p, miR-17-5p, and miR-20a-5p in BC and healthy individuals were evaluated in purpose of finding any association between these miRNAs, HPV infection and cellular genes like TP53, PTEN, and CCND1. Additionally, recognizing a miRNA signature that can differentiate between breast cancer patients and healthy individuals is essential. 2. Materials and Methods 2.1. Sampling In this study, 102 BC patients who had not yet begun chemotherapy, were selected according to our inclusion and exclusion criteria. Besides, 41 normal breast tissue samples were obtained from breast reduction surgeries with normal histopathological results. All tissue samples were immediately stored at − 70°C. The inclusion criteria for this study were: samples from women with approved biopsy evidences of BC, accessibility of fresh samples, and native patients. The exclusion criteria were being under chemotherapy and/or radiotherapy, or hormone therapy procedures either at the time of sampling or before that, any systemic inflammatory diseases, and pregnancy. There were no restrictions regarding the type, stage, or size of tumors, nor on the age of the individuals involved. For control samples, oral contraceptive consumption, smoking, and cervical cancer were exclusion criteria; while not having any history of estrogen therapy was considered as inclusion criteria. To certainly confirm the BC diagnosis, all the results were re-checked by two well experienced pathologists. Tumor Proportion Score (TPS) was more than 50% for all BC samples. We used separate disposable blades for each tissue sections to avoid cross contamination. Peripheral Blood Mononuclear Cells (PBMCs) were isolated from whole blood using density gradient centrifugation by Ficoll (Inno-train, Frankfurt, Germany) from patients and controls. Expression of miRNAs and cellular genes were evaluated in PBMCs. 2.2. HPV detection QIAamp® DNA Mini Kit (Qiagen, Hilden, Germany) was utilized for DNA extraction. To assess the quality of the extracted DNA, a 268-base pair fragment of the β-globin gene was used [ 50 ]. For detecting HPV infection, one primer was utilized to identify the HPV-L1 gene, while a second primer was employed to detect the HPV E6/E7 gene [ 51 ]. 2.3. Quantitative real-time PCR The miRNA Isolation Kit (Favorgen, Taiwan) was applied for RNA extraction. Besides, total RNA extraction was conducted by using RNA purification kit (TaKaRa Bio, Kusatsu, Japan). OD260/OD280 ratio was applied for assessing quantity and Purity of extracted RNA. RNA integrity was evaluated by 1% agarose gel electrophoresis. 2.3.1. Cellular Genes Expression The quantitative assessment of cellular genes including TP53, PTEN, and CCND1 expression was conducted by One-Step RNA PCR Kit (AMV) (TaKaRa Bio, Kusatsu, Japan) and SYBR Green PCR Master Mix (TaKaRa Bio, Kusatsu, Japan). For normalization, GAPDH was used. 2.3.2. miRNAs Expression miRNAs including miR-106b-5p, miR-17-5p, and miR-20a-5p were quantified by Mir-X™ miRNA qRT-PCR TB Green® Kit (TaKaRa Bio, Kusatsu, Japan). All reactions were conducted in triplicate. For relative quantification, SNORD47 and SNORD61 were applied as normalization controls. Moreover, for analysis of relative gene expression data the 2 − ∆∆ CT method was used. 2.4. In-silico analysis 2.4.1. HPV and breast cancer common genes In order to investigate the molecular interactions between HPV infection and breast cancer, we employed the Kyoto Encyclopedia of Genes and Genomes (KEGG) [ 52 – 54 ] database ( https://www.genome.jp/kegg/ ) to identify genes that are involved in both HPV infection (hsa05165) and breast cancer (hsa05224). By cross-referencing these gene inventories, we were able to identify overlapping genes, which revealed shared pathways between the two conditions. Subsequently, we implemented the KEGG Mapper program to conduct pathway enrichment analysis, which illuminated the more extensive biological processes that connect HPV and breast cancer. This integrative approach exposes critical molecular interactions and potential therapeutic targets, thereby offering valuable insights into the pathophysiology of breast cancer and potential avenues for intervention. 2.4.2. microRNA-mRNA interactions The miRTarBase [ 55 ] database ( https://mirtarbase.cuhk.edu.cn/ ) was employed to identify microRNAs that target genes implicated in both the HPV infection and breast cancer pathways. This exhaustive resource allowed us to identify microRNAs that specifically regulate shared genes within these pathways, thereby elucidating critical post-transcriptional regulatory mechanisms. We can acquire valuable insights into the molecular landscape that links HPV infection with breast cancer progression by mapping these microRNA-gene interactions. This improved comprehension of microRNA involvement not only expands our understanding of cancer biology but also emphasizes potential molecular targets for future therapeutic strategies that are designed to disrupt these intersecting pathways. 2.4.3. Bulk RNA sequencing To assess the expression levels of genes implicated in both HPV infection and breast cancer pathways and the microRNAs that target these genes, we analyzed data from the TCGA-BRCA dataset, which was retrieved and examined using the UALCAN online tool ( https://ualcan.path.uab.edu/ ). This approach enabled a comprehensive exploration of gene expression across both normal and cancerous breast tissue samples, as well as among distinct breast cancer subtypes. Using UALCAN [ 56 , 57 ], the expression profiles were effectively visualized, allowing us to gain insight into the extent of dysregulation of these genes in a variety of breast cancer subtypes. This analysis provides a more comprehensive understanding of the molecular changes associated with HPV-related pathways in breast cancer, which may provide insights into subtype-specific patterns and targets for future therapeutic interventions. 2.5. Statistical Methods For the current study, GraphPad Prism version 8 (GraphPad, San Diego, CA, USA) software we used for statistical analysis. To determine normality, quantitative variables were evaluated using the Kolmogorov-Smirnov test. Results were considered statistically significant if the P-value was less than 0.05 (P < 0.05). The data are presented as median values ± standard deviation (SD). For examining expression levels across various groups, we utilized the Kruskal-Wallis test and the Brown-Forsythe test to ensure reliability, particularly in cases where the assumption of equal variances was not met. Additionally, we used ordinary one-way ANOVA for normally distributed data, allowing us to conduct further comparisons among groups whenever significant differences were noted. The discriminatory capacity was assessed using the area under the curve (AUC) with the following classifications: 0.7–0.8 indicates acceptable performance, 0.8–0.9 indicates excellent performance and values greater than 0.9 signify outstanding performance. This analysis was conducted with a 95% confidence interval (CI). All statistical analyses were carried out using SPSS version 23.0 (SPSS, Inc., Chicago, IL, USA). To analyze the relationships between gene expression levels and miRNA profiles, we implemented Spearman correlation coefficients, which helped us measure how closely related those variables were. This comprehensive statistical strategy offered an insightful evaluation of the potential biomarkers associated with breast cancer progression. *Compliance with ethical standards All methods used in this study were carried out in accordance with relevant institutional, national, and international guidelines and regulations. In particular, procedures involving human participants adhered fully to the ethical principles outlined in the Declaration of Helsinki, ensuring the dignity, rights, and well-being of all participants were safeguarded throughout the research. 3. Results 3.1. HPV Prevalence in Breast Cancer group vs. Control group In this case-control study, a total of 102 breast tissue samples from breast cancer patients who had not started chemotherapy were analyzed. The average age of the breast cancer participants was 57.88 ± 5.6 years, with ages ranging from 48 to 74. For the control group, the average age was 55.32 ± 5.04 years, with ages between 44 and 63. The HPV-positive breast cancer subjects had an average age of 59.24 ± 7.8 years, varying from 48 to 74, while the HPV-positive control subjects had a mean age of 55.78 ± 3.49 years, with ages ranging from 48 to 59. No statistically significant differences were observed in the prevalence of HPV between the breast cancer group (24.5% or 25 out of 102) and the control group (19.51% or 8 out of 41) ( p-value = 0.12). There were no statistically significant differences in HPV prevalence between the breast cancer group (24.5% or 25 out of 102) and the control group (21% or 9 out of 41) ( p-value = 0.45). Among the HPV-positive breast cancer cases, HPV-16 and HPV-18 were found as single infections in 13 (52%) and 10 (40%) cases, respectively. Additionally, HPV-16 combined with HPV-18 was identified in 2 samples (8%) of the HPV-positive breast cancer group. In the HPV-positive control group, HPV-16 was detected in 4 samples (44.44%), while HPV-18 was found in 5 samples (55.55%). Furthermore, there was no significant difference in HPV prevalence between the two groups. Differential Expression of TP53, CCND1, and PTEN in Breast Cancer and Control Groups: Implications of HPV Status To examine the expression levels of TP53, CCND1, and PTEN, we considered their levels in six groups: BC patients, control group, HPV positive BC patients, HPV negative BC patients, HPV positive control group, and HPV negative control group. The results shown in Fig. 1 reveals that the expression levels of PTEN in BC group (mean FC ± SD: -1.74 ± 2.91) was significantly lower than the Control group (0 ± 2.03, P: 0.0003 , Fig. 1 B). In addition, the expression levels of TP53 and CCND1 were increased in the BC group compared to the Control group (0.85 ± 1.77 and 3.19 ± 4.54 vs. 0 ± 1.90 and 0 ± 2.92 with a P: 0.04 and P < 0.0001 , respectively, Fig. 1 A and 1 C). Furthermore, following the PCR (molecular) analysis, we divided the samples into four categories: HPV-positive BC, HPV-negative BC, HPV-positive control, and HPV-negative control groups. We then assessed the expression levels of the aforementioned factors in these groups. As illustrated in Fig. 1 , the expression levels of TP53 and PTEN in the HPV-positive BC group were significantly lower than in the HPV-negative BC group (-0.91 ± 1.11 and − 3.44 ± 2.27 vs. 1.45 ± 1.54 and − 1.91 ± 2.89, P < 0.0001 and P: 0.0006 ). The CCND1 expression was considerably lower in the HPV-negative BC group in comparison to HPV-positive BC group (2.69 ± 4.35 vs. 5.13 ± 4.17, P: 0.04 ). However, the expression levels of TP53, PTEN, and CCND1 did not show a significant difference between HPV positive and negative control groups ( P: 0.15 , P: 0.19 , and P: 0.9 respectively). One possible explanation may be the small sample size of the control samples, indicating that further research with a larger sample size is necessary. 3.3. Expression Profile of miR-106b-5p, miR-17-5p, and miR-20a-5p in Breast Cancer Patients: Influence of HPV Status The expression profiles of specific miRNAs in the study groups were analyzed and the all results are presented in Fig. 2 . The findings revealed that breast cancer patients had significantly higher expression levels of miR-106b-5p (1.26 ± 3.56), miR-17-5p (1.19 ± 2.08), and miR-20a-5p (1.69 ± 2.98) compared to the control group (0 ± 2.08, 0 ± 2.41, and 0 ± 2.95, P: 0.02 , P: 0.01 and P: 0.003 , respectively). HPV positive BC patients also had higher expression levels of miR-106b-5p and miR-20a-5p in comparison to HPV negative BC patients (2.70 ± 2.28 and 3.42 ± 2.71 vs. 0.79 ± 3.78 and 1.13 ± 2.87, P: 0.009 and P: 0.002 , respectively). However, no statistically significant difference in miR-17b-5p levels was observed between HPV positive vs. HPV negative BC patients ( P: 0.66 ). Additionally, the expression levels of miR-106b-5p, miR-17-5p, and miR-20a-5p had no statistically significant difference between the HPV positive and negative control groups ( P: 0.7 , P: 0.99 , and P: 0.4 respectively). 3.4. Evaluating TP53, PTEN, CCND1, and Specific miRNAs as Biomarkers in Breast Cancer Patients To investigate whether the levels of TP53, PTEN, CCND1, miR-106b-5p, miR-17-5p, and miR-20a-5p in PBMCs can serve as biomarkers to distinguish breast cancer patients from control subjects, as well as to differentiate HPV-positive breast cancer patients from HPV-negative ones, and to compare HPV-positive controls with HPV-negative controls, we performed a ROC analysis using qPCR results. The ROC curve analysis (Fig. 3 ) indicates that the expression levels of TP53, miR-17-5p, miR-20a-5p and PTEN cannot be considered as even weak biomarkers for screening breast cancer patients, with AUC values of 0.62 ( P: 0.01 ), 0.65 (P: 0.004), 0.65 ( p-value: 0.002 ), and 0.69 ( P: 0.0003 ) respectively. On the other hand, CCND1 which demonstrated an AUC value of and 0.7 ( P: 0.0002 ), can be served as relatively an acceptable biomarker for differentiating between BC and control groups (Fig. 3 A). Furthermore, TP53 (AUC: 0.8, P < 0.0001 ) showed promise as a good biomarker for distinguishing HPV-positive BC cases from HPV-negative ones (Fig. 3 B). However, PTEN (AUC: 0.7, P: 0.0009 ) and miR-20a-5p (AUC: 0.72, P: 0.001 ) were classified as weaker biomarkers for differentiating HPV-positive and HPV negative BC patients. As illustrated in Fig. 3 C, the ROC curve results do not demonstrate any statistically significant AUC value for distinguishing HPV-positive controls from HPV-negative controls. 3.5. Correlation Analysis of Selected miRNAs with TP53, PTEN, and CCND1 The relationship between the fold changes of selected miRNAs (miR-106b-5p, miR-17-5p, and miR-20a-5p) and the aforementioned genes (TP53, PTEN, and CCND1) was analyzed using Spearman correlation test among the study participants (Fig. 4 ). The results indicated a weak yet significant negative correlation between miR-106b-5p, miR-17-5p, and miR-20a-5p with PTEN (r: -0.33, P < 0.0001 ; r: -0.4, P < 0.0001 ; and r: -0.16, P:0.007 , respectively Fig. 4 A, 4 D, 4 G). In contrast, miR-106b-5p showed a weak but statistically significant positive correlation with CCND1 (r: 0.27, P: 0.0007 , Fig. 4 C) and miR-20a-5p also showed a weak positive but statistically significant correlation with TP53 (r: 0.22, P:007, Fig. 4 H). 3.6. In-silico analysis 3.6.1. HPV and breast cancer common genes PTEN, CCND1, and TP53 were identified as critical genes that are common between the HPV infection and breast cancer pathways in our KEGG database analysis (Fig. 5 ). The p53 signaling pathway, human papillomavirus infection, PI3K-Akt signaling, cellular senescence, viral carcinogenesis, and breast cancer are all significantly associated with these genes, as determined by additional pathway enrichment analysis. All of these discoveries provide valuable insights into the intricate molecular interactions that connect HPV infection to breast cancer, indicating that these pathways may serve as potential therapeutic targets. In situations where HPV infection may be a factor, this improved comprehension of the overlapping molecular mechanisms could be crucial in the development of targeted interventions to enhance breast cancer outcomes. 3.6.2. microRNA-mRNA interactions Key microRNAs that target the shared genes implicated in both HPV infection and breast cancer pathways, specifically CCND1, PTEN, and TP53, were identified in our analysis. By employing the miRTarBase database, we identified that hsa-mir-106b, hsa-mir-20a, and hsa-mir-17 are microRNAs that modulate these critical genes. These findings indicate that hsa-mir-106b, hsa-mir-20a, and hsa-mir-17 are vital components of the critical pathways that connect HPV infection with breast cancer (Fig. 6 ), highlighting their potential as molecular targets for therapeutic intervention. This discovery of microRNA-gene interactions offers a foundation for future research into targeted therapies and provides valuable insights into the regulatory networks that underlie cancer pathogenesis. 3.6.3. Expression value Utilizing the UALCAN online tool to analyze data from the TCGA-BRCA dataset, we evaluated the expression levels of critical genes that are involved in both HPV infection and breast cancer pathways, as well as the microRNAs that target these genes. The results of our analysis demonstrated that TP53 and CCND1 were substantially upregulated in breast cancer tissue and across a variety of breast cancer subtypes, underscoring their involvement in tumor progression. On the other hand, PTEN, a critical tumor suppressor gene, was consistently downregulated in breast cancer samples and its subtypes, suggesting a potential loss of inhibitory control over cell growth and survival. Moreover, the microRNAs hsa-mir-106b, hsa-mir-20a, and hsa-mir-17 that target these genes were discovered to be upregulated in breast cancer and its subtypes. TP53, CCND1, and PTEN may be dysregulated as a result of this upregulation of microRNAs, which affects post-transcriptional control over these critical genes. The potential outcome of the elevated levels of hsa-mir-106b, hsa-mir-20a, and hsa-mir-17 is the repression of PTEN and the improper modulation of CCND1 and TP53, which could disrupt cellular processes that are involved in both HPV infection and breast cancer. 4. Discussion BC continues to pose a major global health challenge, accounting for approximately 25% of all malignancies diagnosed in women as of 2020. The rising incidence of BC underscores the pressing need for comprehensive research into its etiological mechanisms and associated risk factors. Among these, the potential involvement of HPV in breast cancer pathogenesis has garnered increasing scientific attention. While a growing body of evidence points toward a possible link between HPV infection and breast tumor development, further in-depth studies are warranted to better characterize the underlying biological interactions and their clinical relevance [ 58 , 59 ]. Dysregulation of gene expression is widely recognized as a key driver of cancer progression. For instance, the downregulation of tumor suppressor genes such as PTEN, alongside the upregulation of oncogenes, plays a pivotal role in promoting tumorigenesis [ 60 , 61 ]. To explore these molecular dynamics, this study employed a combination of in-silico approaches and gene expression profiling, targeting the expression and regulatory interplay of key genes (TP53, PTEN, CCND1) and microRNAs (miR-106b-5p, miR-17-5p, and miR-20a-5p) within the context of HPV-related breast cancer. While PTEN acts as a crucial tumor suppressor, genes and molecules such as CCND1 and miR-106b-5p are known for their proliferative roles [ 62 – 65 ]. TP53, along with miR-17-5p and miR-20a-5p, exhibit more nuanced, dual functions, potentially serving both tumor-suppressive and oncogenic roles depending on the biological context [ 46 , 66 – 68 ]. Cyclin D1, a protein encoded by the CCND1 gene located on chromosome 11q13, is recognized as an oncogenic driver that regulates cell cycle progression and promotes cellular growth, significantly contributing to the pathogenesis of various cancers, including breast cancer [ 62 ]. In our analysis, CCND1 expression was markedly elevated in both BC and HPV-positive BC groups. This observation not only supports our in-silico predictions but also aligns with earlier studies linking CCND1 overexpression to increased cell proliferation [ 35 , 69 ][ 62 – 64 ]. Such overexpression may arise from a variety of deregulating mechanisms, including clonal mutations and disruptions caused by non-coding RNAs [ 70 , 71 ]. Specifically, the HPV E7 oncoprotein promotes degradation of the retinoblastoma protein (pRb), thereby activating E2F transcription factors that upregulate CCND1 expression [ 72 , 73 ]. In parallel, HPV-mediated suppression of tumor-suppressive microRNAs, such as miR-34a, via E6-mediated degradation of p53, allows for unchecked CCND1 expression. Other microRNAs like miR-15a and miR-16-1 are similarly influenced by HPV, further contributing to dysregulation of CCND1 and cell cycle control [ 74 ]. Additionally, we observed a weak but statistically significant positive correlation between CCND1 and miR-106b-5p (r = 0.32, p = 0.04), suggesting potential co-regulatory mechanisms in BC development [ 64 ]. PTEN, a key tumor suppressor, plays an inhibitory role in the PI3K/Akt signaling cascade and facilitates apoptosis by upregulating pro-apoptotic factors. Loss of PTEN function has been widely reported in both primary and metastatic cancers, including breast cancer, and is considered an early event in tumor development [ 75 ]. Our data revealed a consistent downregulation of PTEN expression across both BC and HPV-positive BC samples, suggesting that reduced PTEN levels may facilitate tumor progression. These findings corroborate earlier studies as well as our bioinformatic results [ 76 , 77 ], Although PTEN is not typically identified as a direct target of HPV [ 78 ], indirect modulation through HPV-driven oncogenic pathways appears plausible. For instance, the HPV16 E7 oncoprotein has been shown to interfere with PP2A–p-Akt interactions, maintaining Akt in its active form. Simultaneously, the E6 protein can activate Akt signaling or promote the degradation of TSC2, leading to mTORC1 activation [ 79 ]. These converging mechanisms may collectively suppress PTEN function. Furthermore, the downregulation of PTEN is also associated with the overexpression of certain tumor-promoting microRNAs, including miR-106b-5p, miR-17-5p, and miR-20a-5p, as confirmed by our in-silico analysis. Previous studies have shown that miR-20a-5p targets PTENP1, which positively regulates PTEN expression, while miR-106b-5p and miR-17-5p are capable of directly suppressing PTEN across various cancer types [ 80 ]. Our results are consistent with prior reports indicating that HPV infection is linked to elevated expression of microRNAs such as miR-17-5p, miR-20a-5p, and miR-106b-5p, particularly in cervical cancers [ 81 ]. However, in our study, miR-17-5p did not show statistical significance, potentially due to sample size limitations, highlighting the need for broader investigations. The TP53 gene, located on chromosome 17, encodes the p53 protein, a master regulator of the cellular stress response and a well-established tumor suppressor. Nearly all human cancers exhibit some form of TP53 dysregulation, often due to mutations or functional inactivation, leading to enhanced cell survival, proliferation, and metastasis [ 82 ]. Our data showed significantly elevated TP53 expression in the BC group compared to controls, which aligns with our computational predictions and previous findings [ 83 ].​ Although increased TP53 expression may reflect a compensatory response to DNA damage, it can also indicate the accumulation of dysfunctional, mutant p53 protein [ 84 ][ 85 ]. Notably, HPV-positive BC samples exhibited reduced TP53 expression, a finding that supports existing literature indicating HPV’s role in TP53 suppression [ 2 , 86 ].​ The E6 oncoprotein is known to mediate p53 degradation, thereby reducing TP53 transcript and protein levels in HPV-infected tissues [ 87 ][ 88 ]. Overexpression of miR-20a-5p in HPV-positive samples may also be linked to HPV’s activity, particularly E6-driven upregulation of oncogenic microRNAs [ 89 ]. Both miR-20a-5p and HPV oncogenes E6/E7 influence the TGF-β signaling pathway, hinting at a potential interaction between these regulatory networks [ 49 , 90 ]. The modest yet positive correlation between TP53 and miR-20a-5p observed in our study may reflect their dualistic nature functioning as either tumor suppressors or promoters depending on the context [ 66 , 91 ]. As cancer advances, their oncogenic roles may become more prominent. Our findings reinforce the broader understanding that aberrant expression of specific genes is a hallmark of carcinogenesis. Overexpression of TP53, CCND1, and C-MYC has been consistently linked to human cancers due to their impact on mRNA regulation and tumor progression [ 92 ]. Importantly, genes like TP53 and PTEN, along with microRNAs such as miR-106b-5p and miR-20a-5p, have been proposed as promising therapeutic targets in breast cancer treatment and prevention strategies [ 63 , 66 , 93 , 94 ]. ROC curve analysis further highlighted the diagnostic potential of these biomarkers. CCND1 achieved an AUC of 0.7, indicating clinical relevance for BC detection, while TP53 exhibited superior diagnostic accuracy with an AUC of 0.8, effectively distinguishing HPV-positive from HPV-negative cases. These results align with previous studies validating CCND1 and TP53 as reliable diagnostic markers [ 95 ]. Notably, miR-20a-5p also demonstrated strong diagnostic performance (AUC = 0.72, statistically significant), further supporting its utility as a biomarker [ 86 , 96 ]. Despite these promising insights, certain limitations must be acknowledged. Our study was constrained by a relatively small sample size and a lack of protein-level validation, which may limit the generalizability of the findings. Future research involving larger, more diverse cohorts and longitudinal studies incorporating proteomic assessments will be essential to substantiate and expand upon our current observations. 5. Conclusion In conclusion, the association between HPV infection and breast cancer highlights a concerning intersection that necessitates deeper insights into its underlying molecular mechanisms.​ This study demonstrated significant variations in the expression levels of key oncogenes and tumor suppressor genes, such as TP53, PTEN, and CCND1, alongside specific microRNAs like miR-106b-5p and miR-20a-5p, which appear to be critical in breast cancer progression. These findings suggest that the dysregulation of these genes, driven in part by HPV, could contribute to the malignancy of breast cancer, and the potential biomarkers identified could play an essential role in targeted therapies and early detection strategies. Furthermore, while this research provides valuable contributions to the understanding of how HPV might influence breast cancer development, it also highlights the need for further investigation to confirm these findings. A larger sample size and more comprehensive studies are required to draw definitive conclusions about the relationships identified, especially regarding the clinical applicability of the biomarkers. By advancing the exploration of the intricate connections between HPV, gene expression, and breast cancer, we may uncover new measurements for prevention, diagnosis, and treatment of this prevalent disease. Declarations Acknowledgements The authors are deeply grateful to all the patients who participated in this study. The authors are also grateful to the directors and staff of the participating hospitals for their valuable assistance. Author contributions Zana Naderi : Conceptualization, Methodology, Writing - Original Draft. Malihe Hamidzade : Data curation, Methodology, Software. Amir Hossein Yari : Software, Visualization, Investigation. Hanieh Safarzadeh : Software, Reviewing and Editing. Javid Sadri Nahand : Software, Writing - Original Draft. Marzieh Rezaei : Validation, Writing- Reviewing and Editing. Mohsen Moghoofei : Supervision, Validation, Writing - Review & Editing. Funding statement Not applicable. Conflict of interest disclosure The authors declare that they have no competing interests. Ethics approval and The study was approved by the ethics committee of Kermanshah University of Medical Sciences (KUMS), Kermanshah, Iran under the ethics code of IR.KUMS.MED.REC.1402.174. 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groups.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7269105/v1/08a41bb8cb8914033dc57c8d.jpg"},{"id":89560156,"identity":"ce56c2dd-9be5-4047-9d0d-3f062f636d3e","added_by":"auto","created_at":"2025-08-21 10:18:00","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":168593,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of miR-106b-5p, miR-17-5p, and miR-20a-5p expression levels in breast cancer (BC) patients versus control groups, and between HPV-positive (HPV+) and HPV-negative (HPV-) BC patients, as well as between HPV+ and HPV- control groups.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7269105/v1/b118df7aa53529b34cf1ada4.jpg"},{"id":89564357,"identity":"ed51600f-33d6-42aa-bffa-671ba6902e8e","added_by":"auto","created_at":"2025-08-21 10:34:00","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":148350,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve analysis results for the studied genes and miRNAs in distinguishing between the study groups (AUC: area under the curve; ns: not significant).\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7269105/v1/101694ce6b70db1d28452b82.jpg"},{"id":89560163,"identity":"0833608c-fdc6-4d85-a76b-a2ec1a612d16","added_by":"auto","created_at":"2025-08-21 10:18:00","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":296080,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between TP53, PTEN, and CCND1 with miRNAs (miR-106b-5p, miR-17-5p, and miR-20a-5p) in breast cancer and control groups, highlighting only the significant correlations observed among the factors in the study groups.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7269105/v1/2cd538395b9f815a7abd7910.jpg"},{"id":89562649,"identity":"61745065-efe4-4a44-8f74-33abc496d233","added_by":"auto","created_at":"2025-08-21 10:26:00","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":318075,"visible":true,"origin":"","legend":"\u003cp\u003eHPV and Breast Cancer common genes based on the In-silico analysis: TP53 (A), PTEN (B), and CCND1 (C).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7269105/v1/7a0f97d2a5925e16a96688d7.png"},{"id":89564358,"identity":"a9963cc2-59f0-40c1-89ba-d6bc188c5c47","added_by":"auto","created_at":"2025-08-21 10:34:00","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":288421,"visible":true,"origin":"","legend":"\u003cp\u003eHPV and Breast Cancer common miRNAs based on the In-silico analysis: miR-106b (A), miR-17 (B), and miR-20a (C)\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7269105/v1/90d1703cd7bda78ae597148a.png"},{"id":98814023,"identity":"edc8255b-a7a5-435f-881a-dacc7dc4a2ea","added_by":"auto","created_at":"2025-12-22 16:09:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2511551,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7269105/v1/c4e9fb9e-369b-4c58-bd55-d38213c96650.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Decoding the Relationships Among miRNA, HPV Infection, and Tumor Suppressor Gene Expression in Breast Cancer Patients","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eBreast cancer (BC) is one of the most important causes of cancer related deaths among women worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The occurrence of breast cancer in women has exceeded that of lung, colorectal, prostate, and stomach cancers. Additionally, its incidence has risen due to the growing number of associated risk factors (RFs) [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Among RFs, infectious agents especially noroviruses could be involved as carcinogens or inducers [\u003cspan additionalcitationids=\"CR5 CR6 CR7 CR8\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Numerous studies have explored the impact of viral infections on the development of breast cancer, with HPV being identified as a significant risk factor. This highlights a meaningful connection between the presence of HPV and the occurrence of breast cancer [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The involvement of HPV in breast cancer was assessed by Lonardo \u003cem\u003eet al.\u003c/em\u003e for the first time in 1992 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eHuman Papillomavirus (HPV) is a non-enveloped virus belonging to \u003cem\u003ePapillomaviridae\u003c/em\u003e family with circular double-stranded DNA as the genome [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. HPV is known to be responsible for causing warts and certain types of cancer, as its involvement in these conditions has been clearly affirmed [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In numerous cases of HPV infections, the infection may be resolved on its own within two years. However, in some instances, the infection can persist and lead to precancerous changes and even cancer [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. More than 170 types of HPV have been detected and about 40 types of them are involved in urogenital tract infections and also some types are associated with breast cancer [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. HPV gene products/proteins have the crucial role in tumor development. E6 and E7 oncoproteins are the key factors involved in the virus's ability to cause cancer [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Both E6 and E7 can stimulate tumor development through interactions with p53, retinoblastoma (RB) and Bcl-2 [\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Phosphatase and Tensin Homolog (PTEN) is an enzyme which acts as a tumor suppressor and can be found in almost all human tissues [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. PTEN negatively regulates PI3K pathway which plays a critical role in the development and progression of different types of cancer [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. It has been shown that E6 and E7 proteins can cause downregulation of the PTEN expression in lung cancer cells [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. TP53, which encodes the p53 protein, is also recognized as a tumor suppressor gene. Together with PTEN, it plays essential roles in various biological processes like DNA repair, apoptosis, cell growth, and the progression of the cell cycle. Any dysfunction in these genes or changes in their expression can lead to unchecked tumor cell growth, allowing them to evade signals that normally halt cell division and trigger cell death [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. CCND1, located on the long arm (q) of chromosome 11 at 11q13.3, encodes the Cyclin D1 protein, which is essential for transitioning from the G1 phase to the S phase of the cell cycle [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Additionally, its activity is positively regulated by the Retinoblastoma (RB) protein [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Previous studies have investigated the link between HPV infection and the expression levels of CCND1, revealing that HPV causes a decrease in CCND1 expression [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003emicroRNAs (miR or miRNA) are a class of highly conserved small (about 22 nucleotides) single strand non-coding RNA molecules. Their function is based on being complementary to a part of one or more mRNAs. In animals, miRNAs typically attach to a site in the 3'-UTR of mRNAs, which results in the suppression of translation or the degradation of these mRNAs [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Research indicates that miRNAs play a role in around 60% of gene expression in human cells [\u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. miRNAs influence viral infections and tumor progression in two primary ways, as outlined below: i) Directly: by targeting 3\u0026rsquo;-UTR (untranslated region) of viral oncogene mRNAs; ii) Indirectly: by targeting host cell mRNAs that are connected to normal cellular functions and/or the inhibition or progression of tumors [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan additionalcitationids=\"CR41 CR42\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. miR-106b-5p has an important role in BC development [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. miRNAs may play a role as a regulator of PTEN, as studies have shown that an increase in miR-106b-5p is linked to a decrease in PTEN levels in breast cancer. Additionally, it is also involved in suppressing apoptosis pathways [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. miR-106b-5p overexpression contributes to cell invasion and is associated with 5-fluorouracil resistance in colorectal cancer patients [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. miR-17-5p has been proposed as an anti-HIV factor in some researches, as well as oncomiR in BC in some other studies [\u003cspan additionalcitationids=\"CR47\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. miR-20a-5p is an important miRNA which act as anticancer in some prevalent cancers such as BC. This miRNA is a possible breakthrough for the treatment of these cancers [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Cellular miRNAs can influence the levels of expression of some genes such as TP53, PTEN, and CCND1. Moreover, miRNAs also play a role in the expression of viral oncogenes. Taking these factors into account, examining the relationship between viral gene expression, cellular miRNAs, and cellular genes could enhance our understanding of how BC develops.\u003c/p\u003e\u003cp\u003eIn this study, the expression level of miR-106b-5p, miR-17-5p, and miR-20a-5p in BC and healthy individuals were evaluated in purpose of finding any association between these miRNAs, HPV infection and cellular genes like TP53, PTEN, and CCND1. Additionally, recognizing a miRNA signature that can differentiate between breast cancer patients and healthy individuals is essential.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Sampling\u003c/h2\u003e\u003cp\u003eIn this study, 102 BC patients who had not yet begun chemotherapy, were selected according to our inclusion and exclusion criteria. Besides, 41 normal breast tissue samples were obtained from breast reduction surgeries with normal histopathological results. All tissue samples were immediately stored at \u0026minus;\u0026thinsp;70\u0026deg;C. The inclusion criteria for this study were: samples from women with approved biopsy evidences of BC, accessibility of fresh samples, and native patients. The exclusion criteria were being under chemotherapy and/or radiotherapy, or hormone therapy procedures either at the time of sampling or before that, any systemic inflammatory diseases, and pregnancy. There were no restrictions regarding the type, stage, or size of tumors, nor on the age of the individuals involved. For control samples, oral contraceptive consumption, smoking, and cervical cancer were exclusion criteria; while not having any history of estrogen therapy was considered as inclusion criteria. To certainly confirm the BC diagnosis, all the results were re-checked by two well experienced pathologists. Tumor Proportion Score (TPS) was more than 50% for all BC samples. We used separate disposable blades for each tissue sections to avoid cross contamination.\u003c/p\u003e\u003cp\u003ePeripheral Blood Mononuclear Cells (PBMCs) were isolated from whole blood using density gradient centrifugation by Ficoll (Inno-train, Frankfurt, Germany) from patients and controls. Expression of miRNAs and cellular genes were evaluated in PBMCs.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. HPV detection\u003c/h2\u003e\u003cp\u003eQIAamp\u0026reg; DNA Mini Kit (Qiagen, Hilden, Germany) was utilized for DNA extraction. To assess the quality of the extracted DNA, a 268-base pair fragment of the β-globin gene was used [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. For detecting HPV infection, one primer was utilized to identify the HPV-L1 gene, while a second primer was employed to detect the HPV E6/E7 gene [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Quantitative real-time PCR\u003c/h2\u003e\u003cp\u003eThe miRNA Isolation Kit (Favorgen, Taiwan) was applied for RNA extraction. Besides, total RNA extraction was conducted by using RNA purification kit (TaKaRa Bio, Kusatsu, Japan). OD260/OD280 ratio was applied for assessing quantity and Purity of extracted RNA. RNA integrity was evaluated by 1% agarose gel electrophoresis.\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.3.1. Cellular Genes Expression\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe quantitative assessment of cellular genes including TP53, PTEN, and CCND1 expression was conducted by One-Step RNA PCR Kit (AMV) (TaKaRa Bio, Kusatsu, Japan) and SYBR Green PCR Master Mix (TaKaRa Bio, Kusatsu, Japan). For normalization, \u003cem\u003eGAPDH\u003c/em\u003e was used.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.3.2. miRNAs Expression\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003emiRNAs including miR-106b-5p, miR-17-5p, and miR-20a-5p were quantified by Mir-X\u0026trade; miRNA qRT-PCR TB Green\u0026reg; Kit (TaKaRa Bio, Kusatsu, Japan). All reactions were conducted in triplicate. For relative quantification, SNORD47 and SNORD61 were applied as normalization controls. Moreover, for analysis of relative gene expression data the 2\u003csup\u003e\u0026minus;\u003cem\u003e∆∆\u003c/em\u003eCT\u003c/sup\u003e method was used.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.4. In-silico analysis\u003c/h2\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.4.1. HPV and breast cancer common genes\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eIn order to investigate the molecular interactions between HPV infection and breast cancer, we employed the Kyoto Encyclopedia of Genes and Genomes (KEGG) [\u003cspan additionalcitationids=\"CR53\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genome.jp/kegg/\u003c/span\u003e\u003cspan address=\"https://www.genome.jp/kegg/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to identify genes that are involved in both HPV infection (hsa05165) and breast cancer (hsa05224). By cross-referencing these gene inventories, we were able to identify overlapping genes, which revealed shared pathways between the two conditions. Subsequently, we implemented the KEGG Mapper program to conduct pathway enrichment analysis, which illuminated the more extensive biological processes that connect HPV and breast cancer. This integrative approach exposes critical molecular interactions and potential therapeutic targets, thereby offering valuable insights into the pathophysiology of breast cancer and potential avenues for intervention.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e2.4.2. microRNA-mRNA interactions\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe miRTarBase [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://mirtarbase.cuhk.edu.cn/\u003c/span\u003e\u003cspan address=\"https://mirtarbase.cuhk.edu.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was employed to identify microRNAs that target genes implicated in both the HPV infection and breast cancer pathways. This exhaustive resource allowed us to identify microRNAs that specifically regulate shared genes within these pathways, thereby elucidating critical post-transcriptional regulatory mechanisms. We can acquire valuable insights into the molecular landscape that links HPV infection with breast cancer progression by mapping these microRNA-gene interactions. This improved comprehension of microRNA involvement not only expands our understanding of cancer biology but also emphasizes potential molecular targets for future therapeutic strategies that are designed to disrupt these intersecting pathways.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e2.4.3. Bulk RNA sequencing\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTo assess the expression levels of genes implicated in both HPV infection and breast cancer pathways and the microRNAs that target these genes, we analyzed data from the TCGA-BRCA dataset, which was retrieved and examined using the UALCAN online tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ualcan.path.uab.edu/\u003c/span\u003e\u003cspan address=\"https://ualcan.path.uab.edu/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). This approach enabled a comprehensive exploration of gene expression across both normal and cancerous breast tissue samples, as well as among distinct breast cancer subtypes. Using UALCAN [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], the expression profiles were effectively visualized, allowing us to gain insight into the extent of dysregulation of these genes in a variety of breast cancer subtypes. This analysis provides a more comprehensive understanding of the molecular changes associated with HPV-related pathways in breast cancer, which may provide insights into subtype-specific patterns and targets for future therapeutic interventions.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Statistical Methods\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eFor the current study, GraphPad Prism version 8 (GraphPad, San Diego, CA, USA) software we used for statistical analysis. To determine normality, quantitative variables were evaluated using the Kolmogorov-Smirnov test. Results were considered statistically significant if the P-value was less than 0.05 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The data are presented as median values\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). For examining expression levels across various groups, we utilized the Kruskal-Wallis test and the Brown-Forsythe test to ensure reliability, particularly in cases where the assumption of equal variances was not met. Additionally, we used ordinary one-way ANOVA for normally distributed data, allowing us to conduct further comparisons among groups whenever significant differences were noted. The discriminatory capacity was assessed using the area under the curve (AUC) with the following classifications: 0.7\u0026ndash;0.8 indicates acceptable performance, 0.8\u0026ndash;0.9 indicates excellent performance and values greater than 0.9 signify outstanding performance. This analysis was conducted with a 95% confidence interval (CI). All statistical analyses were carried out using SPSS version 23.0 (SPSS, Inc., Chicago, IL, USA). To analyze the relationships between gene expression levels and miRNA profiles, we implemented Spearman correlation coefficients, which helped us measure how closely related those variables were. This comprehensive statistical strategy offered an insightful evaluation of the potential biomarkers associated with breast cancer progression.\u003c/p\u003e\u003cp\u003e\u003cb\u003e*Compliance with ethical standards\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAll methods used in this study were carried out in accordance with relevant institutional, national, and international guidelines and regulations. In particular, procedures involving human participants adhered fully to the ethical principles outlined in the Declaration of Helsinki, ensuring the dignity, rights, and well-being of all participants were safeguarded throughout the research.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.1. HPV Prevalence in Breast Cancer group vs. Control group\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eIn this case-control study, a total of 102 breast tissue samples from breast cancer patients who had not started chemotherapy were analyzed. The average age of the breast cancer participants was 57.88\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6 years, with ages ranging from 48 to 74. For the control group, the average age was 55.32\u0026thinsp;\u0026plusmn;\u0026thinsp;5.04 years, with ages between 44 and 63. The HPV-positive breast cancer subjects had an average age of 59.24\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8 years, varying from 48 to 74, while the HPV-positive control subjects had a mean age of 55.78\u0026thinsp;\u0026plusmn;\u0026thinsp;3.49 years, with ages ranging from 48 to 59. No statistically significant differences were observed in the prevalence of HPV between the breast cancer group (24.5% or 25 out of 102) and the control group (19.51% or 8 out of 41) (\u003cem\u003ep-value\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.12).\u003c/p\u003e\u003cp\u003eThere were no statistically significant differences in HPV prevalence between the breast cancer group (24.5% or 25 out of 102) and the control group (21% or 9 out of 41) (\u003cem\u003ep-value\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.45). Among the HPV-positive breast cancer cases, HPV-16 and HPV-18 were found as single infections in 13 (52%) and 10 (40%) cases, respectively. Additionally, HPV-16 combined with HPV-18 was identified in 2 samples (8%) of the HPV-positive breast cancer group. In the HPV-positive control group, HPV-16 was detected in 4 samples (44.44%), while HPV-18 was found in 5 samples (55.55%). Furthermore, there was no significant difference in HPV prevalence between the two groups.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eDifferential Expression of TP53, CCND1, and PTEN in Breast Cancer and Control Groups: Implications of HPV Status\u003c/b\u003e\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTo examine the expression levels of TP53, CCND1, and PTEN, we considered their levels in six groups: BC patients, control group, HPV positive BC patients, HPV negative BC patients, HPV positive control group, and HPV negative control group.\u003c/p\u003e\u003cp\u003eThe results shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e reveals that the expression levels of PTEN in BC group (mean FC\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: -1.74\u0026thinsp;\u0026plusmn;\u0026thinsp;2.91) was significantly lower than the Control group (0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.03, \u003cem\u003eP: 0.0003\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). In addition, the expression levels of TP53 and CCND1 were increased in the BC group compared to the Control group (0.85\u0026thinsp;\u0026plusmn;\u0026thinsp;1.77 and 3.19\u0026thinsp;\u0026plusmn;\u0026thinsp;4.54 vs. 0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90 and 0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.92 with a \u003cem\u003eP: 0.04\u003c/em\u003e and \u003cem\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/em\u003e, respectively, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Furthermore, following the PCR (molecular) analysis, we divided the samples into four categories: HPV-positive BC, HPV-negative BC, HPV-positive control, and HPV-negative control groups. We then assessed the expression levels of the aforementioned factors in these groups. As illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the expression levels of TP53 and PTEN in the HPV-positive BC group were significantly lower than in the HPV-negative BC group (-0.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11 and \u0026minus;\u0026thinsp;3.44\u0026thinsp;\u0026plusmn;\u0026thinsp;2.27 vs. 1.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54 and \u0026minus;\u0026thinsp;1.91\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89, \u003cem\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/em\u003e and \u003cem\u003eP: 0.0006\u003c/em\u003e). The CCND1 expression was considerably lower in the HPV-negative BC group in comparison to HPV-positive BC group (2.69\u0026thinsp;\u0026plusmn;\u0026thinsp;4.35 vs. 5.13\u0026thinsp;\u0026plusmn;\u0026thinsp;4.17, \u003cem\u003eP: 0.04\u003c/em\u003e). However, the expression levels of TP53, PTEN, and CCND1 did not show a significant difference between HPV positive and negative control groups (\u003cem\u003eP: 0.15\u003c/em\u003e, \u003cem\u003eP: 0.19\u003c/em\u003e, and \u003cem\u003eP: 0.9\u003c/em\u003e respectively). One possible explanation may be the small sample size of the control samples, indicating that further research with a larger sample size is necessary.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Expression Profile of miR-106b-5p, miR-17-5p, and miR-20a-5p in Breast Cancer Patients: Influence of HPV Status\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe expression profiles of specific miRNAs in the study groups were analyzed and the all results are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The findings revealed that breast cancer patients had significantly higher expression levels of miR-106b-5p (1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;3.56), miR-17-5p (1.19\u0026thinsp;\u0026plusmn;\u0026thinsp;2.08), and miR-20a-5p (1.69\u0026thinsp;\u0026plusmn;\u0026thinsp;2.98) compared to the control group (0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.08, 0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.41, and 0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.95, \u003cem\u003eP: 0.02\u003c/em\u003e, \u003cem\u003eP: 0.01\u003c/em\u003e and \u003cem\u003eP: 0.003\u003c/em\u003e, respectively). HPV positive BC patients also had higher expression levels of miR-106b-5p and miR-20a-5p in comparison to HPV negative BC patients (2.70\u0026thinsp;\u0026plusmn;\u0026thinsp;2.28 and 3.42\u0026thinsp;\u0026plusmn;\u0026thinsp;2.71 vs. 0.79\u0026thinsp;\u0026plusmn;\u0026thinsp;3.78 and 1.13\u0026thinsp;\u0026plusmn;\u0026thinsp;2.87, \u003cem\u003eP: 0.009\u003c/em\u003e and \u003cem\u003eP: 0.002\u003c/em\u003e, respectively). However, no statistically significant difference in miR-17b-5p levels was observed between HPV positive vs. HPV negative BC patients (\u003cem\u003eP: 0.66\u003c/em\u003e). Additionally, the expression levels of miR-106b-5p, miR-17-5p, and miR-20a-5p had no statistically significant difference between the HPV positive and negative control groups (\u003cem\u003eP: 0.7\u003c/em\u003e, \u003cem\u003eP: 0.99\u003c/em\u003e, and \u003cem\u003eP: 0.4\u003c/em\u003e respectively).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e3.4. Evaluating TP53, PTEN, CCND1, and Specific miRNAs as Biomarkers in Breast Cancer Patients\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTo investigate whether the levels of TP53, PTEN, CCND1, miR-106b-5p, miR-17-5p, and miR-20a-5p in PBMCs can serve as biomarkers to distinguish breast cancer patients from control subjects, as well as to differentiate HPV-positive breast cancer patients from HPV-negative ones, and to compare HPV-positive controls with HPV-negative controls, we performed a ROC analysis using qPCR results. The ROC curve analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) indicates that the expression levels of TP53, miR-17-5p, miR-20a-5p and PTEN cannot be considered as even weak biomarkers for screening breast cancer patients, with AUC values of 0.62 (\u003cem\u003eP: 0.01\u003c/em\u003e), 0.65 (P: 0.004), 0.65 (\u003cem\u003ep-value: 0.002\u003c/em\u003e), and 0.69 (\u003cem\u003eP: 0.0003\u003c/em\u003e) respectively. On the other hand, CCND1 which demonstrated an AUC value of and 0.7 (\u003cem\u003eP: 0.0002\u003c/em\u003e), can be served as relatively an acceptable biomarker for differentiating between BC and control groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Furthermore, TP53 (AUC: 0.8, \u003cem\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/em\u003e) showed promise as a good biomarker for distinguishing HPV-positive BC cases from HPV-negative ones (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). However, PTEN (AUC: 0.7, \u003cem\u003eP: 0.0009\u003c/em\u003e) and miR-20a-5p (AUC: 0.72, \u003cem\u003eP: 0.001\u003c/em\u003e) were classified as weaker biomarkers for differentiating HPV-positive and HPV negative BC patients. As illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC, the ROC curve results do not demonstrate any statistically significant AUC value for distinguishing HPV-positive controls from HPV-negative controls.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e3.5. Correlation Analysis of Selected miRNAs with TP53, PTEN, and CCND1\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe relationship between the fold changes of selected miRNAs (miR-106b-5p, miR-17-5p, and miR-20a-5p) and the aforementioned genes (TP53, PTEN, and CCND1) was analyzed using Spearman correlation test among the study participants (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The results indicated a weak yet significant negative correlation between miR-106b-5p, miR-17-5p, and miR-20a-5p with PTEN (r: -0.33, \u003cem\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/em\u003e; r: -0.4, \u003cem\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/em\u003e; and r: -0.16, \u003cem\u003eP:0.007\u003c/em\u003e, respectively Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG). In contrast, miR-106b-5p showed a weak but statistically significant positive correlation with CCND1 (r: 0.27, \u003cem\u003eP: 0.0007\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC) and miR-20a-5p also showed a weak positive but statistically significant correlation with TP53 (r: 0.22, P:007, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e3.6. In-silico analysis\u003c/h2\u003e\u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\u003ch2\u003e3.6.1. HPV and breast cancer common genes\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003ePTEN, CCND1, and TP53 were identified as critical genes that are common between the HPV infection and breast cancer pathways in our KEGG database analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The p53 signaling pathway, human papillomavirus infection, PI3K-Akt signaling, cellular senescence, viral carcinogenesis, and breast cancer are all significantly associated with these genes, as determined by additional pathway enrichment analysis. All of these discoveries provide valuable insights into the intricate molecular interactions that connect HPV infection to breast cancer, indicating that these pathways may serve as potential therapeutic targets. In situations where HPV infection may be a factor, this improved comprehension of the overlapping molecular mechanisms could be crucial in the development of targeted interventions to enhance breast cancer outcomes.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section3\"\u003e\u003ch2\u003e3.6.2. microRNA-mRNA interactions\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eKey microRNAs that target the shared genes implicated in both HPV infection and breast cancer pathways, specifically CCND1, PTEN, and TP53, were identified in our analysis. By employing the miRTarBase database, we identified that hsa-mir-106b, hsa-mir-20a, and hsa-mir-17 are microRNAs that modulate these critical genes. These findings indicate that hsa-mir-106b, hsa-mir-20a, and hsa-mir-17 are vital components of the critical pathways that connect HPV infection with breast cancer (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), highlighting their potential as molecular targets for therapeutic intervention. This discovery of microRNA-gene interactions offers a foundation for future research into targeted therapies and provides valuable insights into the regulatory networks that underlie cancer pathogenesis.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section3\"\u003e\u003ch2\u003e3.6.3. Expression value\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eUtilizing the UALCAN online tool to analyze data from the TCGA-BRCA dataset, we evaluated the expression levels of critical genes that are involved in both HPV infection and breast cancer pathways, as well as the microRNAs that target these genes. The results of our analysis demonstrated that TP53 and CCND1 were substantially upregulated in breast cancer tissue and across a variety of breast cancer subtypes, underscoring their involvement in tumor progression. On the other hand, PTEN, a critical tumor suppressor gene, was consistently downregulated in breast cancer samples and its subtypes, suggesting a potential loss of inhibitory control over cell growth and survival. Moreover, the microRNAs hsa-mir-106b, hsa-mir-20a, and hsa-mir-17 that target these genes were discovered to be upregulated in breast cancer and its subtypes. TP53, CCND1, and PTEN may be dysregulated as a result of this upregulation of microRNAs, which affects post-transcriptional control over these critical genes. The potential outcome of the elevated levels of hsa-mir-106b, hsa-mir-20a, and hsa-mir-17 is the repression of PTEN and the improper modulation of CCND1 and TP53, which could disrupt cellular processes that are involved in both HPV infection and breast cancer.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eBC continues to pose a major global health challenge, accounting for approximately 25% of all malignancies diagnosed in women as of 2020. The rising incidence of BC underscores the pressing need for comprehensive research into its etiological mechanisms and associated risk factors. Among these, the potential involvement of HPV in breast cancer pathogenesis has garnered increasing scientific attention. While a growing body of evidence points toward a possible link between HPV infection and breast tumor development, further in-depth studies are warranted to better characterize the underlying biological interactions and their clinical relevance [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDysregulation of gene expression is widely recognized as a key driver of cancer progression. For instance, the downregulation of tumor suppressor genes such as PTEN, alongside the upregulation of oncogenes, plays a pivotal role in promoting tumorigenesis [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo explore these molecular dynamics, this study employed a combination of in-silico approaches and gene expression profiling, targeting the expression and regulatory interplay of key genes (TP53, PTEN, CCND1) and microRNAs (miR-106b-5p, miR-17-5p, and miR-20a-5p) within the context of HPV-related breast cancer. While PTEN acts as a crucial tumor suppressor, genes and molecules such as CCND1 and miR-106b-5p are known for their proliferative roles [\u003cspan additionalcitationids=\"CR63 CR64\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. TP53, along with miR-17-5p and miR-20a-5p, exhibit more nuanced, dual functions, potentially serving both tumor-suppressive and oncogenic roles depending on the biological context [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan additionalcitationids=\"CR67\" citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCyclin D1, a protein encoded by the CCND1 gene located on chromosome 11q13, is recognized as an oncogenic driver that regulates cell cycle progression and promotes cellular growth, significantly contributing to the pathogenesis of various cancers, including breast cancer [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. In our analysis, CCND1 expression was markedly elevated in both BC and HPV-positive BC groups. This observation not only supports our in-silico predictions but also aligns with earlier studies linking CCND1 overexpression to increased cell proliferation [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e][\u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Such overexpression may arise from a variety of deregulating mechanisms, including clonal mutations and disruptions caused by non-coding RNAs [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. Specifically, the HPV E7 oncoprotein promotes degradation of the retinoblastoma protein (pRb), thereby activating E2F transcription factors that upregulate CCND1 expression [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. In parallel, HPV-mediated suppression of tumor-suppressive microRNAs, such as miR-34a, via E6-mediated degradation of p53, allows for unchecked CCND1 expression. Other microRNAs like miR-15a and miR-16-1 are similarly influenced by HPV, further contributing to dysregulation of CCND1 and cell cycle control [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. Additionally, we observed a weak but statistically significant positive correlation between CCND1 and miR-106b-5p (r\u0026thinsp;=\u0026thinsp;0.32, p\u0026thinsp;=\u0026thinsp;0.04), suggesting potential co-regulatory mechanisms in BC development [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePTEN, a key tumor suppressor, plays an inhibitory role in the PI3K/Akt signaling cascade and facilitates apoptosis by upregulating pro-apoptotic factors. Loss of PTEN function has been widely reported in both primary and metastatic cancers, including breast cancer, and is considered an early event in tumor development [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e]. Our data revealed a consistent downregulation of PTEN expression across both BC and HPV-positive BC samples, suggesting that reduced PTEN levels may facilitate tumor progression. These findings corroborate earlier studies as well as our bioinformatic results [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e], Although PTEN is not typically identified as a direct target of HPV [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e], indirect modulation through HPV-driven oncogenic pathways appears plausible. For instance, the HPV16 E7 oncoprotein has been shown to interfere with PP2A\u0026ndash;p-Akt interactions, maintaining Akt in its active form. Simultaneously, the E6 protein can activate Akt signaling or promote the degradation of TSC2, leading to mTORC1 activation [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. These converging mechanisms may collectively suppress PTEN function. Furthermore, the downregulation of PTEN is also associated with the overexpression of certain tumor-promoting microRNAs, including miR-106b-5p, miR-17-5p, and miR-20a-5p, as confirmed by our in-silico analysis. Previous studies have shown that miR-20a-5p targets PTENP1, which positively regulates PTEN expression, while miR-106b-5p and miR-17-5p are capable of directly suppressing PTEN across various cancer types [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOur results are consistent with prior reports indicating that HPV infection is linked to elevated expression of microRNAs such as miR-17-5p, miR-20a-5p, and miR-106b-5p, particularly in cervical cancers [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. However, in our study, miR-17-5p did not show statistical significance, potentially due to sample size limitations, highlighting the need for broader investigations. The TP53 gene, located on chromosome 17, encodes the p53 protein, a master regulator of the cellular stress response and a well-established tumor suppressor. Nearly all human cancers exhibit some form of TP53 dysregulation, often due to mutations or functional inactivation, leading to enhanced cell survival, proliferation, and metastasis [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]. Our data showed significantly elevated TP53 expression in the BC group compared to controls, which aligns with our computational predictions and previous findings [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e].​ Although increased TP53 expression may reflect a compensatory response to DNA damage, it can also indicate the accumulation of dysfunctional, mutant p53 protein [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e][\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e]. Notably, HPV-positive BC samples exhibited reduced TP53 expression, a finding that supports existing literature indicating HPV\u0026rsquo;s role in TP53 suppression [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e].​ The E6 oncoprotein is known to mediate p53 degradation, thereby reducing TP53 transcript and protein levels in HPV-infected tissues [\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e][\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e]. Overexpression of miR-20a-5p in HPV-positive samples may also be linked to HPV\u0026rsquo;s activity, particularly E6-driven upregulation of oncogenic microRNAs [\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e]. Both miR-20a-5p and HPV oncogenes E6/E7 influence the TGF-β signaling pathway, hinting at a potential interaction between these regulatory networks [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe modest yet positive correlation between TP53 and miR-20a-5p observed in our study may reflect their dualistic nature functioning as either tumor suppressors or promoters depending on the context [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e]. As cancer advances, their oncogenic roles may become more prominent. Our findings reinforce the broader understanding that aberrant expression of specific genes is a hallmark of carcinogenesis. Overexpression of TP53, CCND1, and C-MYC has been consistently linked to human cancers due to their impact on mRNA regulation and tumor progression [\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eImportantly, genes like TP53 and PTEN, along with microRNAs such as miR-106b-5p and miR-20a-5p, have been proposed as promising therapeutic targets in breast cancer treatment and prevention strategies [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e, \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e]. ROC curve analysis further highlighted the diagnostic potential of these biomarkers. CCND1 achieved an AUC of 0.7, indicating clinical relevance for BC detection, while TP53 exhibited superior diagnostic accuracy with an AUC of 0.8, effectively distinguishing HPV-positive from HPV-negative cases. These results align with previous studies validating CCND1 and TP53 as reliable diagnostic markers [\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e]. Notably, miR-20a-5p also demonstrated strong diagnostic performance (AUC\u0026thinsp;=\u0026thinsp;0.72, statistically significant), further supporting its utility as a biomarker [\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDespite these promising insights, certain limitations must be acknowledged. Our study was constrained by a relatively small sample size and a lack of protein-level validation, which may limit the generalizability of the findings. Future research involving larger, more diverse cohorts and longitudinal studies incorporating proteomic assessments will be essential to substantiate and expand upon our current observations.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, the association between HPV infection and breast cancer highlights a concerning intersection that necessitates deeper insights into its underlying molecular mechanisms.​ This study demonstrated significant variations in the expression levels of key oncogenes and tumor suppressor genes, such as TP53, PTEN, and CCND1, alongside specific microRNAs like miR-106b-5p and miR-20a-5p, which appear to be critical in breast cancer progression. These findings suggest that the dysregulation of these genes, driven in part by HPV, could contribute to the malignancy of breast cancer, and the potential biomarkers identified could play an essential role in targeted therapies and early detection strategies.\u003c/p\u003e\u003cp\u003eFurthermore, while this research provides valuable contributions to the understanding of how HPV might influence breast cancer development, it also highlights the need for further investigation to confirm these findings. A larger sample size and more comprehensive studies are required to draw definitive conclusions about the relationships identified, especially regarding the clinical applicability of the biomarkers. By advancing the exploration of the intricate connections between HPV, gene expression, and breast cancer, we may uncover new measurements for prevention, diagnosis, and treatment of this prevalent disease.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are deeply grateful to all the patients who participated in this study. The authors are also grateful to the directors and staff of the participating hospitals for their valuable assistance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eZana Naderi\u003c/em\u003e:\u003c/strong\u003e Conceptualization, Methodology, Writing - Original Draft. \u003cstrong\u003e\u003cem\u003eMalihe Hamidzade\u003c/em\u003e\u003c/strong\u003e: Data curation, Methodology, Software. \u003cstrong\u003e\u003cem\u003eAmir Hossein Yari\u003c/em\u003e\u003c/strong\u003e: Software, Visualization, Investigation. \u003cstrong\u003e\u003cem\u003eHanieh Safarzadeh\u003c/em\u003e\u003c/strong\u003e: Software, Reviewing and Editing. \u0026nbsp;\u003cstrong\u003e\u0026nbsp;\u003cem\u003eJavid Sadri Nahand\u003c/em\u003e\u003c/strong\u003e: Software, Writing - Original Draft. \u003cstrong\u003e\u003cem\u003eMarzieh Rezaei\u003c/em\u003e:\u003c/strong\u003e Validation, Writing- Reviewing and Editing.\u003cstrong\u003e\u003cem\u003e\u0026nbsp;Mohsen Moghoofei\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e:\u003c/em\u003e Supervision, Validation, Writing - Review \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest disclosure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the ethics committee of Kermanshah University of Medical Sciences (KUMS), Kermanshah, Iran under the ethics code of IR.KUMS.MED.REC.1402.174.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient consent\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll subjects (or the person who has the care and custody of the child) signed an informed consent form to participate in the study and a consent form for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study could become\u003c/p\u003e\n\u003cp\u003eavailable through the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSung, H. et al. 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Therapy - Nucleic Acids\u003c/em\u003e. \u003cb\u003e29\u003c/b\u003e, 47\u0026ndash;63 (2022).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Breast cancer, HPV, MicroRNA, Gene expression, Biomarkers","lastPublishedDoi":"10.21203/rs.3.rs-7269105/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7269105/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBreast cancer (BC) is one of the main causes of cancer-related deaths among women, with its incidence rising due to various risk factors (RFs), including viral infections such as Human Papillomavirus (HPV). This study investigates the correlation between HPV infection and the expression levels of key cellular genes, TP53, PTEN, and CCND1, as well as specific microRNAs (miR-106b-5p, miR-17-5p, and miR-20a-5p) in 102 breast cancer patients and 41 healthy controls. Results indicated a higher prevalence of HPV in BC samples; however, the difference in prevalence between BC and control groups was not statistically significant. ​Importantly, TP53 and CCND1 were significantly overexpressed in BC, while PTEN was downregulated.​ The expression levels of CCND1 in HPV-positive BC group was also increased. Further analysis revealed that miR-106b-5p and miR-20a-5p were expressed at elevated levels in HPV-positive BC patients in comparison to their HPV-negative counterparts. All of considered miRNAs were overexpressed in BC group. By using receiver operating characteristic (ROC) analysis, CCND1, plus TP53 and miR-20a-5p emerged as biomarkers for breast cancer diagnosis and differentiation of HPV status respectively. A weak negative correlation between PTEN and three miRNAs, and weak positive correlations between CCND1 and miR-106b-5p and also TP53 and miR-20a-5p were observed. These findings emphasize the potential role of HPV and related biomarkers in the progression of breast cancer, indicating avenues for further research and therapeutic strategies.\u003c/p\u003e","manuscriptTitle":"Decoding the Relationships Among miRNA, HPV Infection, and Tumor Suppressor Gene Expression in Breast Cancer Patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-21 10:17:55","doi":"10.21203/rs.3.rs-7269105/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-19T07:55:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-18T11:28:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-18T07:09:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"312755858173966101518197270411724407064","date":"2025-08-18T06:25:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-17T19:51:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-17T15:44:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"13111136347225725139866002721250749354","date":"2025-08-17T15:41:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"76489147116626569231854565907837544856","date":"2025-08-17T11:07:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"229100386259536356530098772459335359568","date":"2025-08-15T14:30:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"66743831193441335681416446960158184149","date":"2025-08-14T23:25:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"142376853200883480301056646318438256275","date":"2025-08-13T07:29:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-13T07:09:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"224663794987130289134294811849337900824","date":"2025-08-13T04:40:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"134300451541470065286732616113870616424","date":"2025-08-12T17:21:01+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-12T15:33:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-12T15:27:33+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-08T12:32:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-08T05:16:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-08-06T15:22:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7e086883-9789-407a-84b3-a620492b0ff6","owner":[],"postedDate":"August 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":53365865,"name":"Health sciences/Biomarkers"},{"id":53365866,"name":"Biological sciences/Cancer"},{"id":53365867,"name":"Biological sciences/Molecular biology"},{"id":53365868,"name":"Health sciences/Oncology"}],"tags":[],"updatedAt":"2025-12-22T16:03:22+00:00","versionOfRecord":{"articleIdentity":"rs-7269105","link":"https://doi.org/10.1038/s41598-025-26622-9","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-12-21 15:58:30","publishedOnDateReadable":"December 21st, 2025"},"versionCreatedAt":"2025-08-21 10:17:55","video":"","vorDoi":"10.1038/s41598-025-26622-9","vorDoiUrl":"https://doi.org/10.1038/s41598-025-26622-9","workflowStages":[]},"version":"v1","identity":"rs-7269105","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7269105","identity":"rs-7269105","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}