https://orcid.org/0000-0003-3186-8091
Figures
Abstract
MicroRNAs (miRNAs) are small, non-coding RNAs that regulate the expression level of the target genes in the cell. Breast cancer is responsible for the majority of cancer-related deaths among women globally. It has been proven that deregulated miRNAs may play an essential role in the progression of breast cancer. It has been shown in many cancers, including breast cancer, that aberrant expression of miRNAs may be associated with drug resistance. This study investigated the effect of let-7b-5p, detected by bioinformatics methods, on Dox resistance through the Aurora Kinase B (AURKB) gene. In silico analysis using publicly available miRNA expression, GEO datasets revealed that let-7b-5p significantly downregulated in BC. Further in silico studies revealed that of the genes among the potential targets of let-7b-5p, AURKB was the most negatively correlated and may be closely associated with Dox resistance. Expression analysis via quantitative PCR confirmed that let-7b-5p was downregulated and AURKB was upregulated in breast cancer tissue samples. Later, functional studies conducted with MCF-10A, MCF-7, and MDA-MB-231 cell lines demonstrated that let-7b-5p inhibits cancer cells through AURKB and sensitizes them to Dox resistance. In conclusion, it has been shown that the let-7b-5p/AURKB axis may be significant in breast cancer progression and the disruption in this axis may contribute to the trigger of Dox resistance.
Citation: Kaya M, Abuaisha A, Suer I, Emiroglu S, Önder S, Onay Ucar E, et al. (2025) Let-7b-5p sensitizes breast cancer cells to doxorubicin through Aurora Kinase B. PLoS ONE 20(1): e0307420. https://doi.org/10.1371/journal.pone.0307420
Editor: Ruo Wang, Fujian Provincial Hospital, CHINA
Received: July 4, 2024; Accepted: October 31, 2024; Published: January 9, 2025
Copyright: © 2025 Kaya et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All human breast cancer-related microRNA Microarray data files are available from the GEO database, www.ncbi.nlm.nih.gov/geo, (accession numbers: GSE45666, GSE154255, GSE38167). All human breast cancer-related mRNA datasets were collected from TCGA-BRCA (https://portal.gdc.cancer.gov/projects/TCGA-BRCA) and from the GEO database, www.ncbi.nlm.nih.gov/geo (accession numbers: GSE100925 and GSE229571).
Funding: This research was supported by the Council of Higher Education Research Universities Support Program project, ADEP-Istanbul University, TSA-2023-39483. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: -The corresponding author, Dr Zeyneb Kurt, is a member of the editorial board for the PLOS ONE journal. -The rest of the authors have declared that no other competing interests exist.
Introduction
Breast cancer (BC) is a prevalent malignancy resulting in mortality and morbidity among women globally [1,2]. Recurrence and metastases, mostly resulting from BC’s resistance to conventional therapy, are the main causes of mortality among those affected with BC [3]. Many individuals receiving chemotherapy experience a poor initial response or acquired resistance to chemotherapy over time, known as multidrug resistance (MDR) [3,4]. The molecular mechanisms underlying drug resistance in cancers, including BC, are still not fully elucidated. Various alterations in components of pathways for signaling or critical regulators of cell death execution can inhibit the effect of drugs [5]. Understanding the reasons for drug resistance is therefore vital and clinically significant in improving the outcome of BC patients.
MicroRNAs (miRNAs) are approximately 18–24 nucleotides long and have essential functions in post-transcriptional gene regulation [6]. Dysregulation of miRNAs involved in fundamental biological activities such as cell division, proliferation, and apoptosis has been associated with hundreds of diseases, including BC [2,7,8]. Uncovering the relationships between miRNAs and their target genes may be necessary in elucidating disease mechanisms and developing new treatment strategies. Studies show that miRNAs may play roles in various drug resistance mechanisms [9,10]. For example, silencing miR-21, which is overexpressed in BC, has been demonstrated to enhance tamoxifen or fulvestrant sensitivity by inhibiting the PI3K/AKT/mTOR pathway in ER-positive BC cells [11]. Safaei et al. demonstrated that miR-200c increases Doxorubicin (Dox) sensitivity through downregulating MDR1 gene expression in BC cells [12]. Let‐7b-5p, a let-7 family member, is one of the important tumor suppressor miRNAs and regulates the cell cycle. Abnormal reduction in let-7b-5p expression levels has been linked to various cancers, including BC [13–16]. For example, it has been showed that let-7b-5p has a tumor suppressor role in osteosarcoma by blocking IGF1R. Aurora kinase B (AURKB) is a chromosomal passenger protein complex component that regulates cell cycle progression. AURKB deregulation has been detected in various cancers, and its overexpression is commonly associated with tumor cell invasion, metastasis, and drug resistance [17]. However, there is no information about the link between let-7b-5p/AURKB axis and BC. In the present work, analysis of BC-related miRNAs and genes was carried out using the bioinformatics approaches. The expression levels of the chosen miRNA (let-7b-5p) and its potential target gene (AURKB) were validated in BC tissue samples, and the Dox resistance link between the let-7b-5p/AURKB axis was explored using BC cell lines.
Material and methods
Bioinformatics methods utilized for the identification of differentially expressed miRNAs (DEmiRs)
Human breast cancer-related miRNAs were derived from microarray geo datasets GSE45666 (101 tumor samples, 15 adjacent tissue samples), GSE154255 (10 tumor samples, 10 adjacent tissue samples), and GSE38167 (31 tumor samples, 23 adjacent tissue samples) using GEO database (www.ncbi.nlm.nih.gov/geo). Differentially expressed miRNAs (DEmiRNAs) whose expression changed between tumor tissue samples and the adjacent tissues in the datasets were identified with GEO2R (http://www.ncbi.nlm.nih.gov/geo/geo2r) and the parameters were specified to be p < 0.05 and log-fold change (logFC) > 1. The differential expression has been defined as a change in the logFC. A logFC >1 indicates that the miRNAs have changed at least twice (fold change >2.0), suggesting significant differences across groups.
Filtering of miRNAs with prognostic significance in BC
Overlapping DEmiRs between the datasets GSE45666, GSE154255, and GSE38167 were identified. Using KM-plotter (Kmplot) [18], one of the most advanced online survival analysis tools, it was investigated whether the detected miRNAs significantly affected overall survival (OS) of BC. In Kmplot tool, The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) data can be analyzed separately for OS analysis. Kmplot was used to determine the BC-OS relationship of overlapping miRNAs utilizing both TCGA and METABRIC data for further filtering. Separation of patients into high-low-risk level groups has been performed by automated identification of the best cutoff value, which is the default setting in the Kmplot user interface. All potential values among the lower and upper quartiles are explored and the best-performing cutoff, which concludes with the most significant p-value or the highest hazard ratio is selected automatically by the tool.
Determination of the most suitable miRNA for wet lab study
Overlapping miRNAs associated with BC-OS were searched in Pubmed with the keywords "miRNA name, breast cancer". The miRNA with the highest results score was selected as the most suitable miRNA for the wet lab experiments.
Identifying differentially expressed mRNAs (DEMs)
Gene expression differences between tumor and normal tissues were analyzed through Gene Expression Profiling Interactive Analysis 2 (GEPIA2) [19] portal using TCGA-BC data. Genes that met the logFC>2, p<0.001 criteria were considered as DEMs. At the same time, BC-related RNA-seq gene expression datasets GSE100925 (36 tumor and 36 adjacent tissue samples), GSE229571 (6 tumor and 6 adjacent tissue samples) were obtained from the GEO database, and DEMs between tumor tissues and normal tissues were detected using the GEO2R tool (genes with LogFC > 2, p < 0.001 were taken into account).
Identifying matches between overlapping miRNA and genes
Possible target genes of the selected miRNA were examined using the miRNet tool [20]. Overlapping genes were detected between the TCGA-BC, GSE100925, GSE229571 datasets, and the potential targets of let-7b-5p reported by miRNet.
KEGG, GO, and PPI analysis of overlapping genes
Enrichr [21] tool was utilized to carry out Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis on overlapping DEMs. p < 0.05 was selected as the significance level. The protein-protein interaction (PPI) network was created using the Search Tool for the Retrieval of Interacting Genes (STRING) [22] database. The cut-off level was set to a degree > 10.
Correlation analysis of selected miRNA and overlapping genes
The Pearson correlation scores between selected miRNA and overlapping genes were calculated with CancermiRNome [23].
Cancer stage-wise analysis of selected gene
ExplORRNet is a web-based interactive tool [24] for investigating stage-specific miRNA expression patterns and their interactions with mRNA and lncRNA in individuals with breast and gynecological malignancies. ExplORRNet was used to compare selected gene expressions between different stages of BC.
In vitro investigation of selected miRNA and gene
Patient specimens.
Between November 2020 and November 2022, we acquired 72 pairs of human BC samples consisting of tumors and adjacent normal tissues from cases in which breast surgery was performed at the Department of General Surgery, Istanbul Faculty of Medicine Hospital, Istanbul University (Istanbul, Turkey). All patients provided their written informed consent. (Ethics number: 29624016–050.99–903).
Cell lines and culture conditions
MCF-7 and MDA-MB-231 BC cells were gifted by Prof. Dr. Mehmet Topcul Istanbul University, Faculty of Sciences, Department of Biology, and MCF-10A (normal breast epithelial cells) were provided by Prof. Dr. Neslihan Abaci from Istanbul University Aziz Sancar Institute. The MCF-7/Doxorubicin resistance (Dox) and MDA-MB-231/Dox Dox drug-resistant variants of the MCF-7 and MDA-MB-231 cell lines, respectively, were established by stepwise selection at Dox concentrations ranging from 0.5 to 30 μmol/L of parental cells for five months [25].
All cells were cultured in DMEM (EcoTech Biotechnology, Erzurum, Turkey) with 10% FBS (Gibco, Grand Island, NY, USA) and 1% penicillin/streptomycin (Sigma, St. Louis, MO, USA) in a conditioned incubator at 37°C with 5% CO2.
MiRNA mimic transfection and barasertib treatment
All of the cells (parental MCF-7, MDA-MB-231 cells and dox/MCF-7, MDA-MB-231 cells) were seeded at 60% confluence into 96- or 6-well culture plates. After 24 hours, using the supplier’s method for transient 30 nM let-7b-5p mimic or miR-NC (Thermo Fisher Scientific, Waltham, MA, USA), cells were transfected via lipofectamine 3000 reagent (Invitrogen, Carlsbad, CA, USA). AURKB inhibitor Barasertib (Thermo Fisher) dissolved in dimethyl sulfoxide (DMSO). The transfected or treated cells were evaluated after 24, 48, or 72 hours of culture.
qRT-PCR analysis
The relative expression of chosen genes were evaluated using quantitative real-time PCR (qRT-PCR). Total RNA was isolated from matched 72 BC tissue specimens or BC cell lines via TRIzol reagent (Invitrogen, San Diego, CA). A NanoDrop spectrophotometer was used to assess the quality and quantity of RNA samples. To investigate mRNA and miRNA expression levels, equal amounts of RNA from the samples were reverse transcribed into cDNA using a cDNA reverse transcription kit (Thermo Fisher) and TaqMan Kit (Invitrogen), respectively. The qRT-PCR experiments were carried out to detect mRNA expression using 5x HOT FIRE qPCR Mix Plus (Solis-Biodyne, Tartu, Estonia). GAPDH expression was utilized to normalize gene expression. As an internal control, GAPDH was employed for the gene and RNU43 for the miRNA. Each reaction was repeated at least twice. Relative expression was assessed using the 2-ΔΔCt method. Gene sensitivity and specificity were assessed using the receiver operating characteristic (ROC) curve for BC tissue specimens’ qRT-PCR results.
Detection of chemosensitivity
After 24 hours of cultivation in 96-well plates, transfected cells were treated with Dox doses ranging from 0.01 to 120 μM for 48 hours. Cell viability was then assessed using the Cell Counting Kit-8 (EcoTech Biotechnology). The Dox half maximum inhibitory concentration (IC50) values were computed using GraphPad Prism.
Migration assay
The migration capacities of MCF-7/ Dox, MCF-7, MDA-MB-231/ Dox, and MDA-MB-231 cells were assessed using a wound healing experiment. All cells were seeded into each well of a six-well plate and cultivated to 90% confluency. Scraping the plate with a 100 μl pipette tip created a wound in the center of the cell monolayer. Images of the migrated area were captured with an optical microscope at 0 and 48 hours after let-7b-5p mimic transfection and/or AURKB inhibitor treatment. Images of the migrating cells were captured after 48 hours under an inverted microscope.
Western blot analysis
Cells were washed twice with ice-cold PBS after 48 h transfection and collected for further investigation. RIPA protein extraction buffer was used to extract of total proteins (Thermo Fisher). Protein concentration was measured with the SMART TM BCA Protein Assay Kit. Protein samples (25 μg/well) were separated by SDS-PAGE and transferred to PVDF membranes with the Bio-Rad wet tank transfer system. Following 1 hour of blocking with 5% non-fat dry milk (in TBST) at room temperature, the membranes were incubated overnight with primer antibody at 4°C. After washing with TBST, they were incubated with the secondary antibody for 1 hour at room temperature. Following TBST washing, the membranes were examined with a SuperSignal TM West Pico PLUS Chemiluminescent Substrate kit. Anti-GAPDH loading control monoclonal antibody was used for the normalization of data. ImageLab 6.1 software (Bio-Rad Bio-Rad Laboratories, Inc., Hercules, CA, USA) was used to measure band density.
Apoptosis assay
The Annexin V/PI assay was used to evaluate the cells’ apoptosis using the Annexin V-FITC Apoptosis Detection kit (Beckman Coulter). Briefly, cells were obtained using 0.25% trypsin-EDTA, washed twice with cold PBS, and resuspended in a cold binding buffer. Cells were treated for 15 minutes with 3 μl of Annexin V-FITC and 5 μl of propidium-iodide. Beckman Coulter Navios flow cytometer (Navios 3L10) was used for apoptosis examination. 400 microliters of annexin binding buffer was added to the ready cells and read in the Kaluza analysis program. The apoptosis rates (early–late) and necrosis were determined. The results were analyzed and recorded using Kaluza software.
Statistical analysis
The bioinformatics data utilized in the study were gathered from public databases and in silico tools. GraphPad Prism 10 software was used for data analysis and visualization of statistical charts. The Student’s t-test was employed to assess group differences. Values are provided as mean ± standard deviation, with P-values as *P < 0.05, **P < 0.01, ***P < 0.001 indicating statistical significance.
Results
Three BC datasets revealed 19 shared dysregulated miRNAs
We identified 145 miRNAs in the GSE45666, 108 miRNAs in the GSE154255, and 395 miRNAs in the GSE38167 as differentially expressed in tumor vs. normal tissue samples. Among them, 19 differentially expressed miRNAs were shared between the datasets (Table 1 and Fig 1A).
(A) DEmiRNAs shared between the three datasets (B) let-7b-5p had the potential to target a total of 1215 genes, including 14 overlapping genes, according to the miRNet tool. C) Venn diagram of overlapping genes between TCGA-BC data, GSE100925, GSE229571 geo datasets and miRNet-let-7b-5p potential targets. (D) To identify the potential transcription factors associated with overlapping 14 genes, we employed official human gene names, RegNetwork, and P<0.05 criteria in the miRNet tool. The results revealed that there were 80 transcription factors (with 467 edge connections). Nodes in pink: Overlapping genes, nodes on green: Transcription factors.
Let-7b-5p, miR-1290-5p and let-7c-5p were related to a poor prognosis of BC
The effect of overlapping miRNAs on BC-OS was examined using TCGA and METABRIC clinical data. According to the OS analysis results, only three of the 19 overlapping miRNAs were shown to influence BC-OS significantly within both databases (Fig 2, Table 2). An investigation of the relationship between these three miRNAs and BC was conducted in PubMed, and the results showed that these miRNAs were closely connected with BC. As a result, all three miRNAs might be good candidates for future in vitro investigations. Among these three strong candidate miRNAs, let-7b-5p was chosen for further investigation in vitro for the purpose of this research.
The diminished expression of let-7b-5p (A-B) and let-7c-5p (C-D) miRNAs has a negative effect on BC-OS. The increased expression of miR-1290-5p (E-F) also had a harmful impact on BC-OS. Figures (A), (C), and (E) were produced using TCGA-BC data. Figures (B), (D), and (F) were created based on METABRIC data.
(OS analysis was employed via KMplot tool).
14 potential target genes of let-7b-5p with elevated expression, including AURKB, might be essential in BC
Potential target genes of selected let-7b-5p were investigated using the miRNet tool. "Human, miRBase ID, miRTarbase" options are selected in miRNet to detect target genes. Among all, 1215 potential target genes of let-7b-5p were listed. Then, overlapping genes were searched between BC datasets and these 1215 genes. In conclusion, 14 overlapping genes were determined among the dysregulated genes between the GSE100925, GSE229571, TCGA-BC, and let-7b-5p potential targets in miRNet tool (Fig 1B and 1C, and Table 3). The increased expression of these genes within all three datasets might be a key sign of BC.
Overlapping genes may be linked to numerous essential transcription factors
In silico analysis results showed that the 14 overlapping genes may be associated with many important transcription factors including TP53 and MYC, BRCA1, BRCA2, FOXO1 etc. (Fig 1D). The results suggest that because alterations to the expression of 14 genes can affect the expression of many transcription factors, further research into the roles of these genes in BC processes may be critical in understanding the molecular mechanisms underlying disease initiation and development.
Overlapping genes may play important roles in critical processes
The findings of STRING analysis, which analyzed the interaction between overlapping genes, revealed that the interaction between 14 genes was more than expected (p<1.0e-16) (Fig 3A). According to the results of the KEGG research, overlapping genes may have roles in several critical pathways, including the p53 and FoxO signaling pathways (Fig 3B).
(A) STRING Analysis results: Nodes: 14, edges: 89, average node degree: 12.7, avg. local clustering coefficient: 0.98, the expected edges: 8, PPI p-value: < 1.0e-16 (B) Enrichment analysis was performed with 14 official gene names using Enrichr. According to the KEGG 2021 pathway analysis results, it was determined that 14 genes may play a role in important pathways, such as the oocyte maturation p53 signal pathway. (C) Schematic depiction of AURKB, showing the probable let-7b-5p target site. (D) According to TCGA-BC data, the Pearson correlation between let-7b-5p and AURKB expressions was significant (investigated using the CancermiRNome tool). (E) According to TCGA-BC data, AURKB expression was found to be significantly increased in all stages compared to normal tissue (analysis was performed using ExplORRnet).
Findings show that the AURKB gene is a stronger candidate for let-7b-5p
In silico research revealed that let-7b-5p can target AURKB from the 3’UTR region (Fig 3C). Further more it was confirmed using a luciferase reporter assay [26,27]. Using TCGA-BC data, the correlation between let-7b-5p and 14 possible target genes was explored. The AURKB gene was shown to have the highest significant negative correlation among the overlapping genes for let-7b-5p (Fig 3D). Furthermore, the literature research revealed that let-7b-5p/AURKB is associated with drug resistance in some malignancies [26,27]. These in silico and literature data suggest that the let-7b-5p/AURKB axis should be further studied in BC.
AURKB may be an important gene for BC
According to the stage analysis results based on TCGA-BC data, AURKB was shown to be highly expressed in all BC stages. Furthermore, it is noteworthy that AURKB gene expression rises as the stage level increases (Fig 3E). The correlation analysis between the AURKB gene and other overlapping genes demonstrated that all overlapping genes had a strong positive correlation with AURKB (Table 4). These findings suggest that the let-7b-5p/AURKB interaction should be studied further in BC.
In vitro analysis results showed that let-7b-5p and AURKB had opposite expression patterns in BC
Let-7b-5p and AURKB expression levels in patient tumor tissue and adjacent normal tissue samples were investigated by qRT-PCR. The clinicopathological characteristics of the patients are demonstrated in Table 5. The expression level of let-7b-5p was significantly reduced in cancer tissue samples (P < 0.001). On the contrary, AURKB expression was significantly increased in BC tissue samples (P < 0.001) (Fig 4A and 4B). These results were consistent with our in silico analysis results. We also investigated the let-7b-5p and AURKB expression levels in MCF-10A, MCF-7, MCF-7/Dox, MDA-MB-231, and MDA-MB-231/Dox cells using qRT-PCR. Let-7b-5p expression was significantly reduced in all parental BC cancer cells and Dox-resistant BC cells compared to MCF-10A cells (P < 0.05), while AURKB expression was increased (P < 0.05) (Fig 4C and 4D). Furthermore, receiver operating characteristic curve analysis (ROC) showed that let-7b-5p and AURKB expressions may be predictors in BC. The area under the ROC curve for let-7b-5p was 0.893 (95% CI: 0.839–0.946) and for AURKB was 0.849 (95% CI: 0.786–0.911) (Fig 4E and 4F).
Quantification of the relative mRNA expression level of (A) let-7b-5p and (B) AURKB in 72 BC tumor specimens and their matched paracancerous tissue specimens using quantitative PCR. Examination of the (C) let-7b-5p miRNA (D) AURKB mRNA expression levels in different parental and doxorubicin-resistant BC cells. ROC analysis of (E) let-7b-5p and (F) AURKB expressions in BC tissue samples. RNU43 was used as an internal control for miRNA evaluation, and GAPDH was used as an internal control for mRNA evaluation.
Transfecting let-7b-5p mimics efficiently enhanced let-7b-5p in MCF-7/Dox and MDA-MB-231/Dox cells (P < 0.05) (Fig 5A). AURKB expression level was significantly reduced in both let-7b-5p mimic transfected cells and barasertib (AURB inhibitor) treated cells (P < 0.05) (Fig 5B and 5C). Western Blott experiments demonstrated that overexpression of let-7b-5p significantly reduced AURKB protein levels in parental and Dox-resistant cells (Fig 5D). These findings indicated that aberrant expression of let-7b-5p and AURKB may be linked to Dox resistance in BC.
Overexpression of let-7b-5p reduced AURKB expression in BC parental and doxorubicin-resistant cells. (A) The let-7b-5p mimic transfection efficiency was examined by qRT-PCR 24h after transfection. RNU43 was used as an internal control. (B) and (C) Determination of the AURKB mRNA expression levels in parental and doxorubicin-resistant BC cell lines. (D) The protein expression level of AURKB was detected by western blot in cells transfected with let-7b-5p mimics, or miR-NC. GAPDH was used as an internal control in mRNA and protein detection experiments. *P<0.05, **P<0.01, compared with the miR-NC or NC group. MiR-NC: miRNA negative control, NC: Negative control, AURKB inh.: AURKB inhibitor (Barasertib), MCF-7/Dox.: MCF-7 Doxorubicin-resistant cells, MDA-MB-231/Dox.: MDA-MB-231 Doxorubicin-resistant cells.
Overexpression of let-7b-5p or depletion of AURKB increased doxorubicin sensitivity in breast cancer cells
To determine the effects of let-7b-5p or AURKB on the sensitivity of BC cells to Dox, a CCK-8 assay was conducted on MCF-7/Dox and MDA-MB-231/Dox cells transfected with let-7b-5p mimic or AURKB inhibitor. The cells were treated with varying doses of Dox for 48 hours (Fig 6A and 6B). The results showed that overexpression of let-7b-5p or downregulation of AURKB significantly reduced cell viability at different concentrations of Dox and decreased Dox resistance in MCF-7 and MDA-MB-231 cells compared to the control groups (Figs 6C–6F and 7).
IC50 values of (A) Doxorubicin and (B) AURKB inhibitor (Barasertib) in parental and doxorubicin-resistant cells. Relative cell viability (mean ± SD) (C) MCF-7, (D) MCF-7/Dox. (Doxorubicin resistant), (D) MDA-MB-231, (E) MDA-MB-231/Dox. (Doxorubicin resistant) cells of let-7b-5p mimic transfected or AURKB inhibitor-treated with doxorubicin for 48 h.
Light microscopy images of (A) MCF-7, (B) MCF-7/Dox, (C) MDA-MB-231, and (D) MDA-MB-231/Dox cells transfected with let-7b-5p or miR-NC after 48 hours. Let-7b-5p overexpression significantly reduced parental and doxorubicin-resistant cell proliferation compared to control groups. The images were captured at 10x magnification. The bars represent mean ± SD, *p < 0.05. Dox.: Doxorubicin resistant.
Cell migration is a key factor in the occurrence of cancer metastases. A wound healing evaluation assessed the influence of let-7b-5p overexpression and/or AURKB inhibition on cell migration. The results indicated that the wound closure rate was considerably diminished in let-7b-5p transfected and/or AURKB inhibitor-treated Dox-resistant BC cells compared to the miR-NC or NC groups (Figs 8 and 9). Next, we used flow cytometry assay to determine if let-7b-5p-induced Dox sensitivity was associated with apoptosis. The results showed that increased let-7b-5p expression significantly accelerated apoptosis in parental and dox-resistant BC cells (Fig 10). Our findings suggested that let-7b-5p overexpression inhibits BC cells and makes BC cells more sensitive to Dox.
The AURKB inhibitor (Barasertib) reduced migration in (A) doxorubicin-resistant MCF-7 cells and (B) MDA-MB-231 doxorubicin-resistant cells. Furthermore, migration was dramatically reduced in doxorubicin-resistant cells with the combination of transfection of a let-7b-5p mimic and AURKB inhibitor treatment.
Evaluation of the cell migration distances in (A) MCF-7 (B) MCF-7/Dox. cells. Let-7b-5p overexpression in both the parental and doxorubicin-resistant cells significantly reduced migration compared to the control groups.
Overexpression of let-7b-5p promoted apoptosis of (A) MCF-7 and (B) MCF-7/Dox cells **; P < 0.01.
Discussion
Since miRNAs can target numerous genes, miRNA therapy approach can prove to be more advantageous than the single protein target approach [28]. Due to the ability of these compounds to selectively affect many genes within a complex regulatory network, their activities may result in a more extensive and comprehensive therapeutic response [29]. In vitro and in vivo studies have shown that these molecules possess a substantial potential for the cancer treatment in the future [30]. Although miRNA-based therapeutics have potential, they include risks of immunogenicity and safety concerns. The effectiveness of miRNAs specific to targets may be affected by variables like poor RNA stability, uncertain tumor-specific delivery, and localized effects of miRNAs. Despite the advancement of miRNA-targeting medications in clinical trials, none of them have been registered in the clinicaltrials.gov database for the next phase III [30]. It is imperative to have a more precise understanding of the involvement of miRNAs in molecular pathways to solve this challenge. Hence, it is crucial to elucidate the association between miRNAs and their target genes in different types of cancer to facilitate the future utilization of miRNAs as biomarkers and advance the development of therapeutic approaches.
Thousands of potential illness-related miRNAs and genes have been identified using microarray systems and RNA-seq technologies. However, understanding which deregulated genes and/or miRNAs obtained from microarray and RNAseq systems contribute to the disease process is laborious and expensive. Recent advances in bioinformatics methods that facilitate the analysis of microarray and RNA-seq data and the increase in the number of in silico tools developed for the prediction of matches between miRNAs and target genes have made it easier to investigate miRNA-target gene relationships in vitro and in vivo [2].
The examination of GSE45666, GSE154255, and GSE38167 datasets in the bioinformatics section of this work revealed 19 DEmiRNAs in common. After analyzing the BC overall survival relationships of these miRNAs and reviewing the literature, it was determined that the deregulation of let-7b-5p, miR-1290-5p, and let-7c-5p were closely related to BC. When these three miRNAs were searched in Pubmed using the keyword "miRNA name, breast cancer," it turned out that let-7c-5p and miR-1290-5p were connected with BC. Moreover, more information about the association between let-7b-5p and BC was found. Examples to the studies investigating the association between these miRNAs and BC are as follows: Fu et al. demonstrated that let-7c-5p inhibited cell proliferation and promoted cell apoptosis by targeting ERCC6 in BC [31]. Sun et al. found that let-7c-5p inhibits estrogen-activated Wnt signaling in BC stem cell self-renewal stimulation [32]. miR-1290-5p controls the radioresistance of triple-negative BC via inhibiting NLRP3-mediated pyroptosis [33]. miR-1290-5p triggers astrocytes in the brain metastatic microenvironment through the FOXA2/CNTF axis, promoting the spread of brain metastases [34]. Wang et al. demonstrated that overexpressing CDX2 reduced BC by upregulating let-7b-5p and decreasing COL11A1 expression [35]. It was demonstrated that let-7b-5p suppressed the cancer-promoting functions of BC-associated fibroblasts via IL-8 inhibition [36]. These findings indicate that let-7b-5p, miR-1290-5p, and let-7c-5p may play a role in the progression of BC. Although let-7b-5p was chosen for in vitro research in our study, further research on let-7c-5p and miR-1290-5p is recommended since they may have roles in drug resistance and other BC pathways.
Doxorubicin is one of the most widely used drugs in the treatment of BC. However, its effectiveness is not at the desired level due to the drug resistance. let-7b-5p downregulation has been demonstrated in many cancers, including BC [37,38]. Let-7b-5p has been shown to play a role in drug resistance mechanisms in various cancers. For instance, it was shown that the polymorphism in the 3’UTR binding region of the BCL-2 gene, targeted by let-7b, in B-cell lymphoma was associated with fluorouracil resistance of hepatocellular carcinoma [39]. Few studies have shown that let-7b-5p may play a role in Dox resistance in cancers. For example, A single nucleotide polymorphism (SNP) in the let-7b binding in the Bcl-xL gene’s 3’-UTR site has been found to promote resistance to 5-fluorouracil and Dox in BC cells [40]. However, the relationship between let-7b-5p and Dox resistance in BC has not yet been identified.
Previous studies have demonstrated that let-7b-5p directly targets AURKB, leading to a reduction in the expression of this gene at both mRNA and protein levels in different diseases. For instance, Han et al. demonstrated that let-7b-5p reduced cisplatin resistance and tumor development by blocking AURKB in gastric cancer [26]. In another study, Zhou et al. demonstrated that let-7b-5p regulates adriamycin (doxorubicin) resistance via AURKB in chronic myeloid leukemia cells [27]. These findings from the literature demonstrate an important link between let-7b-5p, AURKB, and drug resistance and support our findings.
The AURKB gene is overexpressed in many cancer types including BC [41–43]. Pellizzari et al reported that inhibition of the AURKB pathway may be a promising strategy for the treatment and radiosensitization of Triple Negative Breast Cancer (TNBC) [44]. It has been demonstrated that AURKB stimulates epithelial-mesenchymal transition by stabilizing Snail1, resulting in basal-like breast cancer metastases [45]. AURKB is also closely associated with drug resistance. For instance, Liu et al., revealed that AURKB is related to paclitaxel resistance in BC cells through the PRKCE/RAB27B axis, suggesting a possible intervention target to reverse tumor drug resistance [46]. A different investigation has demonstrated that AURKB facilitates the development of tumors and carboplatin resistance via controlling the ERK pathway in neuroblastoma cells [47]. Some studies have also shown that miRNAs can specifically target AURKB and are associated with drug resistance in cancers. For example, miR-486-5p has been shown to regulate DNA damage inhibition and cisplatin resistance in lung adenocarcinoma via AURKB [48]. The results of these studies indicate that AURKB may be responsible for drug resistance in certain malignancies through various molecular mechanisms, such as miRNAs. The provided research supports that let-7b-5p may be linked to Dox resistance in BC through AURKB.
In current study a comparison of the possible target genes of let-7b-5p in the miRNet tool between TCGA-BC data, GSE100925, and GSE229571 BC GEO datasets revealed 14 genes in common. The STRING analysis revealed a strong link between these 14 genes. Furthermore, a significant association was identified between AURKB and the other 13 genes. These genes have been shown to possess potential oncogenic roles in several malignancies, including BC. For instance, Huang et al. showed that CKS2 overexpression is a poor prognostic marker and promotes cell proliferation and invasion in BC [49]. Overexpression of CKS2 has been shown to enhance the effectiveness of chemotherapy by overriding DNA damage regulators [50]. It has been determined that upregulation of NUSAP1 expression stimulates cell proliferation in invasive BC cells via CDK1 and DLGAP5 and is related to Epirubicin resistance [51]. CCNA2 serves as a possible indicator for immunotherapy in BC and acts as a prognostic indicator for ER+ BC and tamoxifen resistance [52,53]. RRM2 is another prognostic indicator in BC and is associated with worse survival outcomes and tamoxifen resistance [54]. RRM2 silencing with siRNA has been shown to significantly inhibit pancreatic tumor proliferation, either alone or with Dox [55]. CDCA8 is another prominent gene that may be related to AURKB. It is a key modulator of estrogen-induced cell proliferation in BC cells [56]. The AURKB/CDCA8 pathway is potentially pivotal in cancer pathogenesis. Hayama et al. showed that the phosphorylation and activation of CDCA8 by AURKB contribute to human lung carcinogenesis [57]. PLK1, whose increased expression is a major problem in BC, has been reported to mediate resistance to Palbociclib in HR+/HER2- metastatic BC [58]. According to studies, BIRC5 (survivin), an inhibitor of apoptosis (IAP) family member was substantially expressed in BC patients and, it also promotes resistance to chemotherapy, anti-HER2 treatment, and radiotherapy [59]. Mitotic kinases PLK1 and AURKB control BC cell proliferation by phosphorylating BIRC5 [60]. The literature that was assembled here suggests that the molecular linkage of genes connected to AURKB should be examined in more depth. This would allow for a better understanding of the processes that cause drug resistance in BC, as well as the development of novel treatments. Based on these findings, it has been suggested that the let-7b-5p/AURKB axis may affect cancer processes by influencing several key genes.
GEO2R is a web-based tool that is user-friendly and enables users to analyze various data sets from a GEO series in order to identify genes, miRNAs, circRNAs, and other molecules that are differentially expressed. Similarly, miRNet [20] is a web-based platform that is user-friendly and has been specifically designed to assist in the elucidation of miRNA effects by integrating users’ data with existing knowledge through network-based visual analytics. Nevertheless, it is important to keep in mind that the results obtained using GEO2R, miRNET, and other in silico tools in the study may contain data that could restrict the study. For instance, in the GEO2R analysis, some miRNAs, excluded based on logFC and p-value, may have significant relevance in elucidating the link between BC and Dox resistance. In our work, findings based on miRTarbase and Tarbase tools derived from the miRNET tool used to identify the possible target genes of the chosen miRNA (let-7b-5p). For the prediction of miRNA-Gene interactions, other target genes might be proposed for let-7b-5p in tools other than miRTarbase and Tarbase (e.g. miRDB). Thus, it is important to note that, in addition to the miRNAs and genes identified through various GEO datasets and in silico tools, certain significant miRNAs and genes may have been excluded due to the limitations of the bioinformatics methods employed. The investigation provided significant data regarding the relationship between BC Dox resistance/let-7b-5p/AURKB; however, the lack of in vivo experiments represents a different limitation of the study.
In this study, using bioinformatics methods, we determined that let-7b-5p and AURKB may be essential molecules in BC. In silico analysis revealed that AURKB is one of the strongest candidates among the probable targets of let-7b-5p and they exhibit a negative correlation in BC. Thus, we examined let-7b-5p and AURKB expressions in BC and adjacent tissue samples. In accordance with the literature, let-7b-5p was significantly downregulated, and AURKB was upregulated in BC tissue samples. Then, our investigation was conducted into the intricate relationship between let-7b-5p and AURKB and their functional effects on parental BC and Dox-resistant cells. According to our in vitro-study findings, the restoration of let-7b-5p is a potential inhibitor of parental and Dox-resistant cell proliferation, triggering apoptosis and reducing migratory ability. The significant decrease of AURKB at both mRNA and protein levels in let-7b-5p transfected parental and Dox-resistant cells was considered as an important sign that let-7b-5p may function through AURKB in BC cells (Fig 11).
The relationship between miRNAs and target genes in BC doxorubicin resistance was investigated following bioinformatics and wet lab study. In the bioinformatics part publicly available geo datasets were used for DEmiRNAs and DEMs selection. We have identified 19 shared DEmiRNAs in the 3 geo datasets. OS analysis was performed with the Kmplot tool, and it was found that let-7b-5p, miR-1290-5p, and let-7c-5p were significant in BC in both TCGA and METABIRIC data. According to Pubmed, let-7b-5p was chosen for wet lab research because it contained more results about BC associations than the other two miRNAs. DEMs were selected using TCGA-BC, GSE100925 and GSE229571 geo datasets. 14 shared genes (let-7b-5p potential targets) were found. According to the literature review and correlation analysis results, the AURKB gene was chosen as a candidate for wet lab research because it was seen to be more closely related to let-7b-5p among the overlapping genes. In the wet lab part of the study, let-7b-5p and AURKB expression levels were investigated in breast cancer tissue samples and cell lines (parental and/or doxorubicin-resistant). The effect of the let-7b-5p/AURKB axis on cellular processes was investigated by transfecting let-7b-5p mimic parental cells and doxorubicin-resistant cells and/or treating AURKB inhibitor (Barasertib). As a result, our findings showed that let-7b-5p sensitized breast cancer cells to doxorubicin resistance through the AURKB gene.
In conclusion, our findings imply that the let-7b-5p/AURKB/drug resistance link may be in BC. Therefore, it may be vital to conduct deeper investigations on this topic in relation to BC.
Acknowledgments
We thank Prof. Dr. Neslihan Abaci from Istanbul University Aziz Sancar Institute of Experimental Medicine Genetics Department and Prof. Dr. Mehmet Topcul Istanbul University, Faculty of Sciences, Department of Biology, for providing us with cell lines.
References
- 1. Entezari M., Soltani B.M., and Sadeghizadeh M., MicroRNA-203a inhibits breast cancer progression through the PI3K/Akt and Wnt pathways. Sci Rep, 2024. 14(1): p. 4715. pmid:38413784
- 2. Erdogan C., et al., Bioinformatics analysis of the potentially functional circRNA-miRNA-mRNA network in breast cancer. PLoS One, 2024. 19(4): p. e0301995. pmid:38635539
- 3. Gote V., Nookala A.R., Bolla P.K., and Pal D., Drug Resistance in Metastatic Breast Cancer: Tumor Targeted Nanomedicine to the Rescue. Int J Mol Sci, 2021. 22(9). pmid:33925129
- 4. Tufail M., Cui J., and Wu C., Breast cancer: molecular mechanisms of underlying resistance and therapeutic approaches. Am J Cancer Res, 2022. 12(7): p. 2920–2949. pmid:35968356
- 5. Bou Antoun N. and Chioni A.M., Dysregulated Signalling Pathways Driving Anticancer Drug Resistance. Int J Mol Sci, 2023. 24(15). pmid:37569598
- 6. Kaya M., et al., miR-145-5p suppresses cell proliferation by targeting IGF1R and NRAS genes in multiple myeloma cells. Turkish Journal of Biochemistry, 2023. 48(5): p. 563–569.
- 7. Kaya M. and Suer İ., The Effect of miR-34a-5p on Overexpressed AML Associated Genes. Journal of Istanbul Faculty of Medicine, 2023. 86(1): p. 59–68.
- 8. Capik O., et al., CASC11 promotes aggressiveness of prostate cancer cells through miR-145/IGF1R axis. Prostate Cancer and Prostatic Diseases, 2021. 24(3): p. 891–902. pmid:33753875
- 9. Rahman K.U., et al., Mir-153-3p Modulates the Breast Cancer Cells’ Chemosensitivity to Doxorubicin by Targeting KIF20A. Cancers (Basel), 2023. 15(6). pmid:36980610
- 10. Zhang Y., et al., miR-135b-5p enhances doxorubicin-sensitivity of breast cancer cells through targeting anterior gradient 2. J Exp Clin Cancer Res, 2019. 38(1): p. 26. pmid:30665445
- 11. Yu X., et al., Silencing of MicroRNA-21 confers the sensitivity to tamoxifen and fulvestrant by enhancing autophagic cell death through inhibition of the PI3K-AKT-mTOR pathway in breast cancer cells. Biomed Pharmacother, 2016. 77: p. 37–44. pmid:26796263
- 12. Safaei S., et al., miR-200c increases the sensitivity of breast cancer cells to Doxorubicin through downregulating MDR1 gene. Exp Mol Pathol, 2022. 125: p. 104753. pmid:35235816
- 13. Sahin C., Mamillapalli R., Yi K.W., and Taylor H.S., microRNA Let-7b: A Novel treatment for endometriosis. J Cell Mol Med, 2018. 22(11): p. 5346–5353. pmid:30063121
- 14. Asavasupreechar T., et al., PRB inhibited cell proliferation through let-7b-E2F1 in breast cancer. Endocr Relat Cancer, 2023. 30(7). pmid:37130271
- 15. Hui L., et al., MicroRNA let-7b inhibits cell proliferation via upregulation of p21 in hepatocellular carcinoma. Cell Biosci, 2020. 10: p. 83. pmid:32626571
- 16. Suer I. and Kaya M., Is the AURKB Gene Involved in Aml Cell Proliferation Since It is Targeted by miR-34a-5p and let-7b-5p? Konuralp Medical Journal, 2023. 15(1): p. 16–23.
- 17. Borah N.A. and Reddy M.M., Aurora Kinase B Inhibition: A Potential Therapeutic Strategy for Cancer. Molecules, 2021. 26(7). pmid:33915740
- 18. Lánczky A. and Győrffy B., Web-Based Survival Analysis Tool Tailored for Medical Research (KMplot): Development and Implementation. J Med Internet Res, 2021. 23(7): p. e27633. pmid:34309564
- 19. Tang Z., et al., GEPIA2: an enhanced web server for large-scale expression profiling and interactive analysis. Nucleic Acids Res, 2019. 47(W1): p. W556–w560. pmid:31114875
- 20. Chang L., Zhou G., Soufan O., and Xia J., miRNet 2.0: network-based visual analytics for miRNA functional analysis and systems biology. Nucleic Acids Res, 2020. 48(W1): p. W244–w251. pmid:32484539
- 21. Kuleshov M.V., et al., Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res, 2016. 44(W1): p. W90–7. pmid:27141961
- 22. Szklarczyk D., et al., The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res, 2023. 51(D1): p. D638–d646. pmid:36370105
- 23. Li R., et al., CancerMIRNome: an interactive analysis and visualization database for miRNome profiles of human cancer. Nucleic Acids Res, 2022. 50(D1): p. D1139–d1146. pmid:34500460
- 24. Lawarde A., et al., ExplORRNet: An interactive web tool to explore stage-wise miRNA expression profiles and their interactions with mRNA and lncRNA in human breast and gynecological cancers. Noncoding RNA Res, 2024. 9(1): p. 125–140. pmid:38035042
- 25. Kovalchuk O., et al., Involvement of microRNA-451 in resistance of the MCF-7 breast cancer cells to chemotherapeutic drug doxorubicin. Mol Cancer Ther, 2008. 7(7): p. 2152–9. pmid:18645025
- 26. Han X., et al., Let-7b attenuates cisplatin resistance and tumor growth in gastric cancer by targeting AURKB. Cancer Gene Ther, 2018. 25(11–12): p. 300–308. pmid:30237418
- 27. Zhou X., et al., Let-7b regulates the adriamycin resistance of chronic myelogenous leukemia by targeting AURKB in K562/ADM cells. Leuk Lymphoma, 2020. 61(14): p. 3451–3459. pmid:32856506
- 28. Kaya M., Bioinformatics evaluation of the circRNA–miRNA–mRNA axis in cervical squamous cell carcinoma. Exploration of Medicine, 2024. 5: p. 553–565.
- 29. Mishra S., Yadav T., and Rani V., Exploring miRNA based approaches in cancer diagnostics and therapeutics. Crit Rev Oncol Hematol, 2016. 98: p. 12–23. pmid:26481951
- 30. Pagoni M., et al., miRNA-Based Technologies in Cancer Therapy. J Pers Med, 2023. 13(11). pmid:38003902
- 31. Fu X., et al., Let-7c-5p inhibits cell proliferation and induces cell apoptosis by targeting ERCC6 in breast cancer. Oncol Rep, 2017. 38(3): p. 1851–1856. pmid:28731186
- 32. Sun X., et al., Let-7c blocks estrogen-activated Wnt signaling in induction of self-renewal of breast cancer stem cells. Cancer Gene Ther, 2016. 23(4): p. 83–9. pmid:26987290
- 33. Li Y. and Li X., miR-1290 modulates the radioresistance of triple-negative breast cancer by targeting NLRP3-mediated pyroptosis. Clin Transl Oncol, 2022. 24(9): p. 1764–1775.
- 34. Sirkisoon S.R., et al., Breast cancer extracellular vesicles-derived miR-1290 activates astrocytes in the brain metastatic microenvironment via the FOXA2→CNTF axis to promote progression of brain metastases. Cancer Lett, 2022. 540: p. 215726.
- 35. Wang H., et al., Over-expression of CDX2 alleviates breast cancer by up-regulating microRNA let-7b and inhibiting COL11A1 expression. Cancer Cell Int, 2020. 20: p. 13. pmid:31938021
- 36. Al-Harbi B., Hendrayani S.F., Silva G., and Aboussekhra A., Let-7b inhibits cancer-promoting effects of breast cancer-associated fibroblasts through IL-8 repression. Oncotarget, 2018. 9(25): p. 17825–17838. pmid:29707149
- 37. Li L., et al., Let-7b-5p inhibits breast cancer cell growth and metastasis via repression of hexokinase 2-mediated aerobic glycolysis. Cell Death Discov, 2023. 9(1): p. 114. pmid:37019900
- 38. Dai Y., et al., Let-7b-5p inhibits colon cancer progression by prohibiting APC ubiquitination degradation and the Wnt pathway by targeting NKD1. Cancer Sci, 2023. 114(5): p. 1882–1897. pmid:36445120
- 39. Ma J., et al., Let-7b binding site polymorphism in the B-cell lymphoma-extra large 3’UTR is associated with fluorouracil resistance of hepatocellular carcinoma. Mol Med Rep, 2015. 11(1): p. 677–81. pmid:25333670
- 40. Wang T., et al., A let-7b binding site SNP in the 3’-UTR of the Bcl-xL gene enhances resistance to 5-fluorouracil and doxorubicin in breast cancer cells. Oncol Lett, 2015. 9(4): p. 1907–1911. pmid:25789066
- 41. Li L., et al., AURKB promotes bladder cancer progression by deregulating the p53 DNA damage response pathway via MAD2L2. J Transl Med, 2024. 22(1): p. 295. pmid:38515112
- 42. Wang H., Pan H., and Huang X., AURKB Enhances Chromosomal Remodeling of Telomeric Genes and Accelerates Tumorigenesis of Uveal Melanoma. Invest Ophthalmol Vis Sci, 2023. 64(4): p. 23. pmid:37079315
- 43. Kaya M., et al., Overexpression of CDC25A, AURKB, and TOP2A Genes Could Be an Important Clue for Luminal A Breast Cancer. Eur J Breast Health, 2024. 20(4): p. 284–291. pmid:39323324
- 44. Pellizzari S., Athwal H., Bonvissuto A.C., and Parsyan A., Role of AURKB Inhibition in Reducing Proliferation and Enhancing Effects of Radiotherapy in Triple-Negative Breast Cancer. Breast Cancer (Dove Med Press), 2024. 16: p. 341–346. pmid:39006183
- 45. Zhang J., et al., Aurora B induces epithelial-mesenchymal transition by stabilizing Snail1 to promote basal-like breast cancer metastasis. Oncogene, 2020. 39(12): p. 2550–2567. pmid:31996785
- 46. Liu M., Li Y., Zhang C., and Zhang Q., Role of aurora kinase B in regulating resistance to paclitaxel in breast cancer cells. Hum Cell, 2022. 35(2): p. 678–693. pmid:35088239
- 47. Yang Y., et al., AURKB promotes tumorigenesis and carboplatin resistance by regulating the ERK pathway in neuroblastoma cells. Int J Neurosci, 2023. 133(11): p. 1224–1232. pmid:34396896
- 48. Sun G., et al., microRNA-486-5p Regulates DNA Damage Inhibition and Cisplatin Resistance in Lung Adenocarcinoma by Targeting AURKB. Crit Rev Eukaryot Gene Expr, 2024. 34(4): p. 13–23. pmid:38505869
- 49. Huang N., et al., Overexpression of CKS2 is associated with a poor prognosis and promotes cell proliferation and invasion in breast cancer. Mol Med Rep, 2019. 19(6): p. 4761–4769. pmid:30957190
- 50. del Rincón S.V., et al., Cks overexpression enhances chemotherapeutic efficacy by overriding DNA damage checkpoints. Oncogene, 2015. 34(15): p. 1961–7. pmid:24858038
- 51. Zhang X., Pan Y., Fu H., and Zhang J., Nucleolar and Spindle Associated Protein 1 (NUSAP1) Inhibits Cell Proliferation and Enhances Susceptibility to Epirubicin In Invasive Breast Cancer Cells by Regulating Cyclin D Kinase (CDK1) and DLGAP5 Expression. Med Sci Monit, 2018. 24: p. 8553–8564. pmid:30476929
- 52. Wang Y., et al., Integrated Profiling Identifies CCNA2 as a Potential Biomarker of Immunotherapy in Breast Cancer. Onco Targets Ther, 2021. 14: p. 2433–2448.
- 53. Gao T., et al., CCNA2 is a prognostic biomarker for ER+ breast cancer and tamoxifen resistance. PLoS One, 2014. 9(3): p. e91771. pmid:24622579
- 54. Putluri N., et al., Pathway-centric integrative analysis identifies RRM2 as a prognostic marker in breast cancer associated with poor survival and tamoxifen resistance. Neoplasia, 2014. 16(5): p. 390–402. pmid:25016594
- 55. Zheng S., et al., siRNA Knockdown of RRM2 Effectively Suppressed Pancreatic Tumor Growth Alone or Synergistically with Doxorubicin. Mol Ther Nucleic Acids, 2018. 12: p. 805–816. pmid:30153565
- 56. Bu Y., et al., CDCA8 is a key mediator of estrogen-stimulated cell proliferation in breast cancer cells. Gene, 2019. 703: p. 1–6. pmid:30953709
- 57. Hayama S., et al., Phosphorylation and activation of cell division cycle associated 8 by aurora kinase B plays a significant role in human lung carcinogenesis. Cancer Res, 2007. 67(9): p. 4113–22. pmid:17483322
- 58. Guerrero-Zotano Á., et al., CCNE1 and PLK1 Mediate Resistance to Palbociclib in HR+/HER2- Metastatic Breast Cancer. Clin Cancer Res, 2023. 29(8): p. 1557–1568. pmid:36749874
- 59. Adinew G.M., Messeha S., Taka E., and Soliman K.F.A., The Prognostic and Therapeutic Implications of the Chemoresistance Gene BIRC5 in Triple-Negative Breast Cancer. Cancers (Basel), 2022. 14(21). pmid:36358602
- 60. Garlapati C., et al., PLK1 and AURKB phosphorylate survivin differentially to affect proliferation in racially distinct triple-negative breast cancer. Cell Death Dis, 2023. 14(1): p. 12. pmid:36627281