Polymorphisms in AURKA and AURKB are associated with the survival of triple-negative breast cancer patients treated with taxane-based adjuvant chemotherapy

Deciphering the miRNA-mRNA Interaction Landscape between Breast Cancer and Triple-Negative Breast Cancer: An Integrated Bioinformatics Approach

Breast cancer (BC) is globally recognized as the second most prevalent form of cancer. It predominantly affects women and can be categorized into distinct types based on the overexpression of specific cancer receptors.The key receptors implicated in this context are the human epidermal growth factor receptor-2 (HER2), estrogen receptor (ER), and progesterone receptor (PR), alongside a particularly intricate subclass known as triple-negative breast cancer (TNBC). This subclassification is critical for the stratification of breast cancer and informs therapeutic decision-making processes. Due to a lack of therapeutic targets, such as growth factor receptors, TNBC is the most aggressive type. Hence, identifying targetable regulators such as miRNAs could pave the way for potential therapeutic interventions. To identify common differentially expressed mRNAs (DE-mRNAs) in BC, including TNBC, we leveraged two data sets from the GEO collection and The Cancer Genome Atlas (TCGA). Significant DE-mRNAs were identified through PPI, MCODE, CytoNCA, and CytoHubba analyses. Following this, miRNAs were predicted using mirDIP. We utilized GSE42568, GSE185645, and TCGA and identified 159 common DE-mRNAs. Using Cytoscape plug-ins, we identified the 10 most significant DE-mRNAs in BC. Using mirDIP, target miRNAs for 10 DE-mRNAs were identified. We conducted an advanced analysis on the TNBC GEO data set (GSE45498) to corroborate the significance of shared DE-mRNAs and DE-miRNAs in TNBC. We identified four downregulated DE-miRNAs, including hsa-miR-802, hsa-miR-1258, hsa-miR-548a-3p, and hsa-miR-2053, significantly associated with TNBC. Our study revealed significant miRNA-mRNA interactions, specifically hsa-miR-802/MELK, hsa-miR-1258/NCAPG, miR-548a-3p/CCNA2, and hsa-miR-2053/NUSAP1, in both BC and TNBC. The observed downregulation of hsa-miR-548a-3p is associated with diminished survival rates in BC patients, emphasizing their potential utility as prognostic indicators. Furthermore, the differential expression of mRNAs, including CCNB2, UBE2C, MELK, and KIF2C, correlates with reduced survival outcomes, signifying their critical role as potential targets for therapeutic intervention in both BC and TNBC. These findings highlight specific regulatory mechanisms that are potentially crucial for understanding and treating these cancer types.

Transcriptomic analysis revealed potential regulatory biomarkers and repurposable drugs for breast cancer treatment

Breast cancer (BC) is the most widespread cancer worldwide. Over 2 million new cases of BC were identified in 2020 alone. Despite previous studies, the lack of specific biomarkers and signaling pathways implicated in BC impedes the development of potential therapeutic strategies. We employed several RNAseq datasets to extract differentially expressed genes (DEGs) based on the intersection of all datasets, followed by protein-protein interaction network construction. Using the shared DEGs, we also identified significant gene ontology (GO) and KEGG pathways to understand the signaling pathways involved in BC development. A molecular docking simulation was performed to explore potential interactions between proteins and drugs. The intersection of the four datasets resulted in 146 DEGs common, including AURKB, PLK1, TTK, UBE2C, CDCA8, KIF15, and CDC45 that are significant hub-proteins associated with breastcancer development. These genes are crucial in complement activation, mitotic cytokinesis, aging, and cancer development. We identified key microRNAs (i.e., hsa-miR-16-5p, hsa-miR-1-3p, hsa-miR-147a, hsa-miR-195-5p, and hsa-miR-155-5p) that are associated with aggressive tumor behavior and poor clinical outcomes in BC. Notable transcription factors (TFs) were FOXC1, GATA2, FOXL1, ZNF24 and NR2F6. These biomarkers are involved in regulating cancer cell proliferation, invasion, and migration. Finally, molecular docking suggested Hesperidin, 2-amino-isoxazolopyridines, and NMS-P715 as potential lead compounds against BC progression. We believe that these findings will provide important insight into the BC progression as well as potential biomarkers and drug candidates for therapeutic development.

Overexpression of Aurora Kinase B Is Correlated with Diagnosis and Poor Prognosis in Hepatocellular Carcinoma

Aurora kinase B (AURKB) overexpression promotes tumor initiation and development by participating in the cell cycle. In this study, we focused on the mechanism of AURKB in hepatocellular carcinoma (HCC) progression and on AURKB's value as a diagnostic and prognostic biomarker in HCC. We used data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) to analyze AURKB expression in HCC. We found that the expression levels of AURKB in HCC samples were higher than those in the corresponding control group. R packages were used to analyze RNA sequencing data to identify AURKB-related differentially expressed genes (DEGs), and these genes were found to be significantly enriched during the cell cycle. The biological function of AURKB was verified, and the results showed that cell proliferation was slowed down and cells were arrested in the G2/M phase when AURKB was knocked down. AURKB overexpression resulted in significant differences in clinical symptoms, such as the clinical T stage and pathological stage. Kaplan-Meier survival analysis, Cox regression analysis, and Receiver Operating Characteristic (ROC) curve analysis suggested that AURKB overexpression has good diagnostic and prognostic potential in HCC. Therefore, AURKB may be used as a potential target for the diagnosis and cure of HCC.

Recent Updates on Oncogenic Signaling of Aurora Kinases in Chemosensitive, Chemoresistant Cancers: Novel Medicinal Chemistry Approaches for Targeting Aurora Kinases

The Aurora Kinase family (AKI) is composed of serine-threonine protein kinases involved in the modulation of the cell cycle and mitosis. These kinases are required for regulating the adherence of hereditary-related data. Members of this family can be categorized into aurora kinase A (Ark-A), aurora kinase B (Ark-B), and aurora kinase C (Ark-C), consisting of highly conserved threonine protein kinases. These kinases can modulate cell processes such as spindle assembly, checkpoint pathway, and cytokinesis during cell division. The main aim of this review is to explore recent updates on the oncogenic signaling of aurora kinases in chemosensitive/chemoresistant cancers and to explore the various medicinal chemistry approaches to target these kinases. We searched Pubmed, Scopus, NLM, Pubchem, and Relemed to obtain information pertinent to the updated signaling role of aurora kinases and medicinal chemistry approaches and discussed the recently updated roles of each aurora kinases and their downstream signaling cascades in the progression of several chemosensitive/chemoresistant cancers; subsequently, we discussed the natural products (scoulerine, Corynoline, Hesperidin Jadomycin-B, fisetin), and synthetic, medicinal chemistry molecules as aurora kinase inhibitors (AKIs). Several natural products' efficacy was explained as AKIs in chemosensitization and chemoresistant cancers. For instance, novel triazole molecules have been used against gastric cancer, whereas cyanopyridines are used against colorectal cancer and trifluoroacetate derivatives could be used for esophageal cancer. Furthermore, quinolone hydrazine derivatives can be used to target breast cancer and cervical cancer. In contrast, the indole derivatives can be preferred to target oral cancer whereas thiosemicarbazone-indole could be used against prostate cancer, as reported in an earlier investigation against cancerous cells. Moreover, these chemical derivatives can be examined as AKIs through preclinical studies. In addition, the synthesis of novel AKIs through these medicinal chemistry substrates in the laboratory using in silico and synthetic routes could be beneficial to develop prospective novel AKIs to target chemoresistant cancers. This study is beneficial to oncologists, chemists, and medicinal chemists to explore novel chemical moiety synthesis to target specifically the peptide sequences of aurora kinases in several chemoresistant cancer cell types.

Gene expression profile analysis to discover molecular signatures for early diagnosis and therapies of triple-negative breast cancer

Triple-negative breast cancer (TNBC) is one of the most lethal subtypes of breast cancer (BC), and it accounts for approximately 10%-20% of all invasive BCs diagnosed worldwide. The survival rate of TNBC in stages III and IV is very low, and a large number of patients are diagnosed in these stages. Therefore, the purpose of this study was to identify TNBC-causing molecular signatures and anti-TNBC drug agents for early diagnosis and therapies. Five microarray datasets that contained 304 TNBC and 109 control samples were collected from the Gene Expression Omnibus (GEO) database, and RNA-Seq data with 116 tumor and 124 normal samples were collected from TCGA database to identify differentially expressed genes (DEGs) between TNBC and control samples. A total of 64 DEGs were identified, of which 29 were upregulated and 35 were downregulated, by using the statistical limma R-package. Among them, seven key genes (KGs) were commonly selected from microarray and RNA-Seq data based on the high degree of connectivity through PPI (protein-protein interaction) and module analysis. Out of these seven KGs, six KGs (TOP2A, BIRC5, AURKB, ACTB, ASPM, and BUB1B) were upregulated and one (EGFR) was downregulated. We also investigated their differential expression patterns with different subtypes and progression stages of BC by the independent datasets of RNA-seq profiles from UALCAN database, which indicated that they may be potential biomarkers for early diagnosis. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses with the proposed DEGs were performed using the online Enrichr database to investigate the pathogenetic processes of TNBC highlighting KGs. Then, we performed gene regulatory network analysis and identified three transcriptional (SOX2, E2F4, and KDM5B) and three post-transcriptional (hsa-mir-1-3p, hsa-mir-124-3p, and hsa-mir-34a-5p) regulators of KGs. Finally, we proposed five KG-guided repurposable drug molecules (imatinib, regorafenib, pazopanib, teniposide, and dexrazoxane) for TNBC through network pharmacology and molecular docking analyses. These drug molecules also showed significant binding performance with some cancer-related PTM-sites (phosphorylation, succinylation, and ubiquitination) of top-ranked four key proteins (EGFR, AURKB, BIRC5, and TOP2A). Therefore, the findings of this computational study may play a vital role in early diagnosis and therapies against TNBC by wet-lab validation.

Piperine Increases Pentagamavunon-1 Anti-cancer Activity on 4T1 Breast Cancer Through Mitotic Catastrophe Mechanism and Senescence with Sharing Targeting on Mitotic Regulatory Proteins

Pentagamavunon-1 performs more potent anti-cancer effects than curcumin against various cancer cells, but it remains to be optimized. Piperine shows the activity as an enhancer of a therapeutic agent. This study expects to achieve higher effectiveness of PGV-1 on 4T1 breast cancer cells through co-treatment with piperine with exploring the effect of cytotoxicity, mitotic catastrophe, cellular senescence, and target proteins of PGV-1 and piperine on the regulation of mitosis in TNBC cells (4T1). The assays emphasize MTT assay, May Grünwald-Giemsa staining, SA-β-galactosidase assay, and bioinformatics analysis, respectively, to elicit the respected activities. The results revealed that PGV-1 performed a cytotoxic effect with an IC50 value of 9 µM while piperine showed a lower cytotoxic effect with an IC50 value of 800 µM on 4T1 cells 24 h treatment. However, the combination treatment of both showed a synergistic cytotoxic enhancement effect with an average CI value < 1. Furthermore, the combination of PGV-1 and piperine induced mitotic catastrophe and senescence better than the single treatment. Treatment of 1 µM of PGV-1 and 400 µM of piperine increased the percentage of senescent cells by 33%. Bioinformatics analysis revealed that PGV-1 and piperine target proteins play a role in mitotic regulation, namely CDK1, KIF11, AURKA, AURKB, and PLK1, to contribute to mitotic catastrophe. Therefore, piperine increases the effectiveness of PGV-1 to suppress 4T1 cells growth synergistically that may occur through mitotic catastrophe and senescence targeting on mitotic regulatory proteins.

Identification of prognostic genes for early basal-like breast cancer with weighted gene co-expression network analysis

BACKGROUND

Breast cancer (BC) has become the leading cause of death for women's malignancies and increasingly threatens the health of women worldwide. However, there is a lack of effective targeted drugs for basal-like BC. Therefore, biomarkers related to the prognosis of early BC need to be identified.

METHODS

The RNA-seq data of 87 cases of early basal-like BC and 111 cases of normal breast tissue from The Cancer Genome Atlas were explored by the weighted gene co-expression network analysis method and Limma package. Then, intersected genes were identified, and hub genes were selected by the maximal clique centrality method. The prognostic effect of the hub genes was also evaluated in early basal-like BC.

RESULTS

In total, 601 IGs were identified in this study. An APPI network was constructed, and the top 10 hub genes were selected, namely, cyclin B1, cyclin A2, cyclin-dependent kinase 1, cell division cycle 20, DNA topoisomerase II alpha, BUB1 mitotic checkpoint serine/threonine kinase, aurora kinase B (AURKB), cyclin B2, kinesin family member 11, and assembly factor for spindle microtubules. Only AURKB was found to be significantly associated with the overall prognosis of early basal-like BC. The immune cell infiltration analysis showed that the infiltration numbers of CD4 + T cells and naïve CD8 + T cells were positively correlated with the AURKB expression level, while those of naïve B cells and macrophage M2 cells were negatively correlated with the AURKB expression level in basal-like BC.

CONCLUSION

AURKB might be a potential prognostic indicator in early basal-like BC.

Aurora Kinase A Is an Independent Predictor of Invasive Recurrence in Breast Ductal Carcinoma in situ

INTRODUCTION

Aurora Kinase A (AURKA/STK15) has a role in centrosome duplication and is a regulator of mitotic cell proliferation. It is over-expressed in breast cancer and other cancers, however; its role in ductal carcinoma in situ (DCIS) remains to be defined. This study aims to characterize AURKA protein expression in DCIS and evaluate its prognostic significance.

METHODS

AURKA was assessed immunohistochemically in a large well-characterized cohort of DCIS (n = 776 pure DCIS and 239 DCIS associated with invasive breast cancer [DCIS-mixed]) with long-term follow-up data (median = 105 months) and basic molecular characterization.

RESULTS

High AURKA expression was observed in 15% of DCIS cases and was associated with features of aggressiveness including larger tumour size, high nuclear grade, hormone receptor negativity, HER2 positivity, and high Ki67 proliferation index. AURKA expression was higher in DCIS associated with invasive breast cancer than in pure DCIS (p < 0.0001). In the DCIS-mixed cohort, the invasive component showed higher AURKA expression than the DCIS component (p < 0.0001). Outcome analysis revealed that AURKA was a predictor of invasive recurrence (p = 0.002).

CONCLUSION

High AURKA expression is associated with poor prognosis in DCIS and might be a potential marker to predict DCIS progression to invasive disease.

Molecular markers associated with the outcome of tamoxifen treatment in estrogen receptor-positive breast cancer patients: scoping review and in silico analysis

Tamoxifen (TMX) is used as adjuvant therapy for estrogen receptor-positive (ER+) breast cancer cases due to its affinity and inhibitory effects. However, about 30% of cases show drug resistance, resulting in recurrence and metastasis, the leading causes of death. A literature review can help to elucidate the main cellular processes involved in TMX resistance. A scoping review was performed to find clinical studies investigating the association of expression of molecular markers profiles with long-term outcomes in ER+ patients treated with TMX. In silico analysis was performed to assess the interrelationship among the selected markers, evaluating the joint involvement with the biological processes. Forty-five studies were selected according to the inclusion and exclusion criteria. After clustering and gene ontology analysis, 23 molecular markers were significantly associated, forming three clusters of strong correlation with cell cycle regulation, signal transduction of proliferative stimuli, and hormone response involved in morphogenesis and differentiation of mammary gland. Also, it was found that overexpression of markers in selected clusters is a significant indicator of poor overall survival. The proposed review offered a better understanding of independent data from the literature, revealing an integrative network of markers involved in cellular processes that could modulate the response of TMX. Analysis of these mechanisms and their molecular components could improve the effectiveness of TMX.

Bioinformatics Analysis Identifies IL6ST as a Potential Tumor Suppressor Gene for Triple-Negative Breast Cancer

Improved insight into the molecular mechanisms of triple-negative breast cancer (TNBC) is required to predict prognosis and develop a new therapeutic strategy for targeted genes. The aim of this study was to identify genes significantly associated with TNBC and further analyze their prognostic significance. The Cancer Genome Atlas (TCGA) TNBC database and gene expression profiles of GSE76275 from Gene Expression Omnibus (GEO) were used to explore differentially co-expressed genes in TNBC compared with those in normal tissues and non-TNBC breast cancer tissues. Differential gene expression and weighted gene co-expression network analyses identified 24 differentially co-expressed genes. Functional annotation suggested that these genes were primarily enriched in processes such as metabolism, membrane, and protein binding. The protein-protein interaction (PPI) network further identified ten hub genes, five of which (MAPT, CBS, SOX11, IL6ST, and MEX3A) were confirmed to be differentially expressed in an independent dataset (GSE38959). Moreover, CBS and MEX3A expression was upregulated, whereas IL6ST expression was downregulated in TNBC tissues compared to that in other breast cancer subtypes. Furthermore, lower expression of IL6ST was associated with worse overall survival in patients with TNBC. Thus, IL6ST might play an important role in TNBC progression and could serve as a tumor suppressor gene for diagnosis and treatment.

The impact of Aurora kinase A genetic polymorphisms on cervical cancer progression and clinicopathologic characteristics

The aims of this study were to explore the involvement of Aurora kinase A (AURKA) gene single nucleotide polymorphisms (SNPs) in uterine cervical cancer that has not yet been investigated. One hundred and six patients with cervical invasive cancer and 94 patients with precancerous lesions, and 302 Taiwanese female individuals were included. AURKA SNPs rs2273535, rs6024836, rs2064863 and rs1047972 were analyzed for genotypic distributions using real-time polymerase chain reaction. There were no statistically significant differences in the genetic frequencies of AURKA SNPs among patients with invasive cancer and those with precancerous lesions of uterine cervix and control women. There were no associations among AURKA SNPs and clinicopathologcal variables and recurrence and survival events. However, in a multivariate analysis, cervical cancer patients with adenocarcinoma (HR: 3.18, 95% CI: 1.23-8.23; p=0.017) and larger tumor (HR: 5.61, 95% CI: 2.10-14.95; p=0.001) had poorer recurrence-free survival. In conclusion, tumor size and pelvic lymph node status rather than AURKA SNPs were the most obvious independent parameter that could significantly predict 5 years survival rate in Taiwanese women with cervical cancer.

Tanshinone Inhibits NSCLC by Downregulating AURKA Through Let-7a-5p

Lung cancer is the most deadly malignancy in the last decade, accounting for about 1.6 million deaths every year globally. Tanshinone is the constituent of Salvia miltiorrhiza; it has been found that they influence tumorigenesis. However, the role of tanshinones on lung cancer is still not clear. Let-7a-5p, a short non-coding RNA, is regarded as a suppressor gene in tumorigenesis. Herein, we verified that let-7a-5p is significantly downregulated in non-small-cell lung cancer (NSCLC) tissues and cell lines. Tanshinone suppressed the expression of aurora kinase A (AURKA), inhibited cell proliferation, and arrested cell cycle progression. Our results showed that tanshinones suppressed NSCLC by upregulating the expressions of let-7a-5p via directly targeting AURKA. Besides, the data reveal that the knockdown of AURKA can also inhibit cell proliferation, arrest cell cycle, and promote cell apoptosis. Furthermore, this study demonstrates that AURKA was negatively correlated with let-7a-5p in NSCLC patient tissues. Taken together, our findings suggest that tanshinone inhibits NSCLC by downregulating AURKA through let-7a-5p. Tanshinones and let-7a-5p have the potential to be candidates for drug development of NSCLC. In conclusion, this study revealed that tanshinones with miRNA linking lead to partial mechanism in NSCLC.

Analysis of differentially expressed mRNAs and the prognosis of cholangiocarcinoma based on TCGA database

Background

The effective evaluation of cholangiocarcinoma (CCA) is challenging due to a lack of accurate screening tools. Consequently, there is an urgent need to screen out effective biomarkers. Bioinformatics analysis on a substantial amount of transcriptomic data to screen biomolecules allows for the verification of histological samples, and can provide a new method for CCA biomolecule screening in diagnosis and prognosis.

Methods

EdgeR model was used to analyze The Cancer Genome Atlas (TCGA)-extracted CCA data set, and to determine the differential expression of mRNAs. Based on this, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to perform functional and pathway enrichment analysis. Subsequently, a protein interaction network was also established to identify the key differential node genes. Then, the previously determined differential genes were analyzed to establish a link between these genes and clinical prognosis. Finally, we used tissue samples to realize our results via IHC, Western blot and qRT-PCR.

Results

A total of 5,561 differential mRNAs were screened, including 3,473 upregulated genes and 2,088 downregulated genes. GO and KEGG enrichment analysis showed that the upregulated genes had significantly enriched cell adhesion, concentrated chromosomal motility, and microtubule motility. Downregulated genes were significantly enriched in heterologous metabolism and exosomes. Furthermore, we found upregulated genes were significantly enriched in the cancer pathways and cell cycle. Downregulated genes were enriched in the metabolic pathways and biosynthesis of antibiotics. Ten hub genes were screened out through the protein interaction network; among these, the AURKB and PLK1 genes were closely related to the clinical prognosis of patients. Results of the immunohistochemical staining, Western blot and qRT-PCR all showed that the expression of AURKB and PLK1 in cancer tissues was higher than that in the adjacent tissues, and this difference was statistically significant (P<0.05).

Conclusions

The upregulated genes were significantly enriched in the biological processes of cell division, cell cycle, and related cell components. AURKB and PLK1 play a key role in differentially expressed gene nodes. These genes are closely related to the prognosis of patients and can be used as potential diagnostic tools and prognostic biomarkers.

Identification of Aurora Kinase A as a Biomarker for Prognosis in Obesity Patients with Early Breast Cancer

BACKGROUND

Obesity is associated both with a higher risk of developing breast cancer, particularly in postmenopausal women, and with worse disease outcome for women of all ages. Previous investigation suggested Aurora A kinase was able to partially restore the functionalities of obese adipose-derived mesenchymal stem cells by stabilizing their primary cilia and reestablishing a balance of multiple stemness-associated genes. The association between Aurora A and obesity breast cancer is still unclear. We hypothesized that overexpression of Aurora A was associated with poor survival in obesity breast cancer and the related axis mechanism was involved.

METHODS

A total of 517 primary breast cancer specimens were collected from the First Affiliated Hospital of China Medical University between January 2011 and November 2016. Our independent variable was BMI at baseline, categorized as overweight (BMI ≥25 kg/m2, as obesity cohort), and normal (18.5 ≤ BMI <25 kg/m2, as non-obesity cohort). The immunohistochemical (IHC) staining was performed with Aurora A, Survivin, MMP11, Cyclin B1, and Cathepsin L. Kaplan-Meier curve was used to analyze overall survival in our cohorts and TCGA-BRCA data (GSE3494). Log rank test was used to calculate P values. Protein-protein interaction (PPI) network analysis and MCODE model were used to analyze the Aurora-altered signal pathway from GSE78958.

RESULTS

Among 517 breast patients, Aurora A-positive (staining scores ≥4) was significantly higher in obesity breast carcinoma compared with non-obesity cancer carcinoma (χ 2=9.79, P=0.002), with more frequency in hormone receptor-negative (68.4% vs 77.9%, P=0.015) and HER2-positive patients (28.7% vs 17.9%, P=0.003). High Aurora A expression was remarkably and significantly associated with overall survival (OS) (8-year OS ratio: 69.5% vs 81.1%, OR=1.76, 95% CI: 1.03~3.02, P=0.041) in obesity cohort. Interestingly, higher expression of Aurora A was not associated with a shorter overall survival time among the non-obesity breast cancer (8-year OS ratio: 81.4% vs 85.8%, OR=1.40, 95% CI: 0.79~2.45, P=0.229). As for RFS, the expression levels of Aurora A expression genes have no significance with RFS statistically in non-obesity and obesity patients. Aurora A and lymph node metastases were significantly poor prognostic factors for OS, and borderline significance was noted for high BMI. Kaplan-Meier survival analysis from TCGA database confirmed that the high Aurora A expression group had worse prognosis (HR=1.47, 95% CI: 1.14-1.90, P=0.003). The KEGG pathway enrichment results were consistent with GO biological process term analysis, in which CCNB1 was enriched for upregulated Aurora A. In our samples, Aurora A level on tumor cytoplasm had broad connections with Cyclin B1 by IHC correlation analysis (correlation coefficient = 0.227, P=0.001).

CONCLUSION

Our finding demonstrates here for the first time that high expression of Aurora A was notably correlated with early recurrence and poor overall survival in obesity patients with early breast cancer. The Aurora A-Cyclin B1 axis could be a potential promising therapeutic target for cancer intervention and therapy.

A framework for transcriptome-wide association studies in breast cancer in diverse study populations

BACKGROUND

The relationship between germline genetic variation and breast cancer survival is largely unknown, especially in understudied minority populations who often have poorer survival. Genome-wide association studies (GWAS) have interrogated breast cancer survival but often are underpowered due to subtype heterogeneity and clinical covariates and detect loci in non-coding regions that are difficult to interpret. Transcriptome-wide association studies (TWAS) show increased power in detecting functionally relevant loci by leveraging expression quantitative trait loci (eQTLs) from external reference panels in relevant tissues. However, ancestry- or race-specific reference panels may be needed to draw correct inference in ancestrally diverse cohorts. Such panels for breast cancer are lacking.

RESULTS

We provide a framework for TWAS for breast cancer in diverse populations, using data from the Carolina Breast Cancer Study (CBCS), a population-based cohort that oversampled black women. We perform eQTL analysis for 406 breast cancer-related genes to train race-stratified predictive models of tumor expression from germline genotypes. Using these models, we impute expression in independent data from CBCS and TCGA, accounting for sampling variability in assessing performance. These models are not applicable across race, and their predictive performance varies across tumor subtype. Within CBCS (N = 3,828), at a false discovery-adjusted significance of 0.10 and stratifying for race, we identify associations in black women near AURKA, CAPN13, PIK3CA, and SERPINB5 via TWAS that are underpowered in GWAS.

CONCLUSIONS

We show that carefully implemented and thoroughly validated TWAS is an efficient approach for understanding the genetics underpinning breast cancer outcomes in diverse populations.

Identification of Hub Genes Using Co-Expression Network Analysis in Breast Cancer as a Tool to Predict Different Stages

Background

Breast cancer has a high mortality rate and is the most common cancer of women worldwide. Our gene co-expression network analysis identified the genes closely related to the pathological stage of breast cancer.

Material/Methods

We performed weighted gene co-expression network analysis (WGCNA) from the Gene Expression Omnibus (GEO) database, and performed pathway enrichment analysis on genes from significant modules.

Results

A non-metastatic sample (374) of breast cancer from GSE102484 was used to construct the gene co-expression network. All 49 hub genes have been shown to be upregulated, and 19 of the 49 hub genes are significantly upregulated in breast cancer tissue. The roles of the genes CASC5, CKAP2L, FAM83D, KIF18B, KIF23, SKA1, GINS1, CDCA5, and MCM6 in breast cancer are unclear, so in order to better reveal the staging of breast cancer markers, it is necessary to study those hub genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes indicated that 49 hub genes were enriched to sister chromatid cohesion, spindle midzone, microtubule motor activity, cell cycle, and something else. Additionally, there is an independent data set – GSE20685 – for module preservation analysis, survival analysis, and gene validation.

Conclusions

This study identified 49 hub genes that were associated with pathologic stage of breast cancer, 19 of which were significantly upregulated in breast cancer. Risk stratification, therapeutic decision making, and prognosis predication might be improved by our study results. This study provides new insights into biomarkers of breast cancer, which might influence the future direction of breast cancer research.

AURKB: a promising biomarker in clear cell renal cell carcinoma

Background

Aurora kinase B (AURKB) is an important carcinogenic factor in various tumors, while its role in clear cell renal cell carcinoma (ccRCC) still remains unclear. This study aimed to investigate its prognostic value and mechanism of action in ccRCC.

Methods

Gene expression profiles and clinical data of ccRCC patients were downloaded from The Cancer Genome Atlas database. R software was utilized to analyze the expression and prognostic role of AURKB in ccRCC. Gene set enrichment analysis (GSEA) was used to analyze AURKB related signaling pathways in ccRCC.

Results

AURKB was expressed at higher levels in ccRCC tissues than normal kidney tissues. Increased AURKB expression in ccRCC correlated with high histological grade, pathological stage, T stage, N stage and distant metastasis (M stage). Kaplan-Meier survival analysis suggested that high AURKB expression patients had a worse prognosis than patients with low AURKB expression levels. Multivariate Cox analysis showed that AURKB expression is a prognostic factor of ccRCC. GSEA indicated that genes involved in autoimmune thyroid disease, intestinal immune network for IgA production, antigen processing and presentation, cytokine-cytokine receptor interaction, asthma, etc., were differentially enriched in the AURKB high expression phenotype.

Conclusions

AURKB is a promising biomarker for predicting prognosis of ccRCC patients and a potential therapeutic target. In addition, AURKB might regulate progression of ccRCC through modulating intestinal immune network for IgA production and cytokine-cytokine receptor interaction, etc. signaling pathways. However, more research is necessary to validate the findings.

Aurora kinase A stabilizes FOXM1 to enhance paclitaxel resistance in triple-negative breast cancer

Triple-negative breast cancer (TNBC) has a relatively poor outcome. Acquired chemoresistance is a major clinical challenge for TNBC patients. Previously, we reported that kinase-dead Aurora kinase A (Aurora-A) could effectively transactivate the FOXM1 promoter. Here, we demonstrate an additional pathway through which Aurora-A stabilizes FOXM1 by attenuating its ubiquitin in TNBC. Specifically, Aurora-A stabilizes FOXM1 in late M phase and early G1 phase of the cell cycle, which promotes proliferation of TNBC cells. Knock-down of Aurora-A significantly suppresses cell proliferation in TNBC cell lines and can be rescued by FOXM1 overexpression. We observe that paclitaxel-resistant TNBC cells exhibit high expression of Aurora-A and FOXM1. Overexpression of Aurora-A offers TNBC cells an additional growth advantage and protection against paclitaxel. Moreover, Aurora-A and FOXM1 could be simultaneously targeted by thiostrepton. Combination of thiostrepton and paclitaxel treatment reverses paclitaxel resistance and significantly inhibits cell proliferation. In conclusion, our study reveals additional mechanism through which Aurora-A regulates FOXM1 and provides a new therapeutic strategy to treat paclitaxel-resistant triple-negative breast cancer.