Literature DB >> 30288111

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

Yuqian Liao1, Yulu Liao2, Jun Li2, Junyu Li2, Ying Fan3, Binghe Xu3.   

Abstract

PURPOSE: Triple-negative breast cancer (TNBC) is more than a single disease. Identifying biomarkers to further subdivide TNBC patients with distinct outcome is of great importance. It has been reported that single-nucleotide polymorphisms (SNPs) in Aurora kinase A (AURKA) or Aurora kinase B (AURKB) are associated with the risk and survival of several cancers. But till now, there is no research about these polymorphisms in TNBC patients.
MATERIALS AND METHODS: In this study, we investigated the association between polymorphisms in AURKA or AURKB gene and prognosis of TNBC patients treated with taxane-based adjuvant chemotherapy. A total of 273 TNBC patients were enrolled. Haploview 4.2 software was used to identify Tag SNPs. Genotyping was conducted using the MassARRAY MALDI-TOF system.
RESULTS: We found that AURKA rs6099128 GG genotype carriers had significantly worse overall survival (OS) than TT+ TG genotype carriers (P = 0.003, HR = 12.499, 95% CI = 2.357-66.298). AURKB rs11651993 TT genotype carriers had better disease-free survival (DFS) than TC + CC genotype carriers (P = 0.018, HR = 1.876, 95% CI = 1.116-3.154). AURKB rs2289590 CC genotype carriers had worse DFS than CA + AA genotype carriers (P = 0.021, HR = 0.536, 95% CI = 0.315-0.912). After subgroup analysis, rs11651993 TC + CC genotype predicted worse DFS in subgroups of age ≤ 50, post-menopausal, grade unknown (UK), tumor size >2 cm, and lymph node negative. Rs2289590 CA + AA genotype could predict favorable DFS in pre-menopausal, grade 3 and lymph node-positive patients.
CONCLUSION: We first demonstrated that polymorphisms in AURKA or AURKB gene might predict the OS or DFS of TNBC patients treated with taxane-based adjuvant chemotherapy.

Entities:  

Keywords:  Aurora kinase; TNBC; polymorphism; prognosis

Year:  2018        PMID: 30288111      PMCID: PMC6159783          DOI: 10.2147/CMAR.S174735

Source DB:  PubMed          Journal:  Cancer Manag Res        ISSN: 1179-1322            Impact factor:   3.989


Introduction

Breast cancer is the most common cancer and is the leading cause of cancer death in women around the world.1 It is a very heterogeneous disease and is divided into several subgroups that have different clinicopathological characteristics and prognosis.2 Triple- negative breast cancer (TNBC) is defined as lacking expression of estrogen receptor (ER), progesterone receptor (PR), and epidermal growth factor receptor 2 (HER2). It is characterized by aggressive behavior, onset at young age, and early relapse.3,4 TNBC is insensitive to endocrine and HER2-targeted therapy, and therefore, chemotherapy remains the mainstay of treatment. Although some clinical trials found that TNBC is more sensitive to platinum-based chemotherapy,5,6 taxane/anthracycline-based regimens are still standard and preferred regimens for TNBC patients in the adjuvant setting.7 However, not all TNBC patients respond to chemotherapy, which suggests that TNBC is more than a single disease.8 Identifying biomarkers to further subdivide TNBC patients with distinct outcome is of great importance. Aurora kinase A (AURKA) and Aurora kinase B (AURKB) are members of the Aurora kinase subfamily of conserved serine/threonine kinases.9 AURKA localizes to the duplicate centrosomes from the beginning of S phase, shifts to the bipolar spindle microtubules during mitosis, and, finally, moves to perinuclear materials of the daughter cells at the end of mitosis.10 By contrast, AURKB starts at early G2 and localizes to the chromosomes in prophase, the centromere in prometaphase and metaphase, the central spindle in anaphase, and the mid-body in cytokinesis.11 AURKA plays a critical role in centrosome duplication and maturation.12,13 AURKB plays a key role during mitosis by regulating chromosomal alignment, segregation, and cytokinesis, as the catalytic protein of the chromosomal passenger complex (CPC).11 Deregulation of Aurora kinases leads to impairment of mitotic spindle checkpoints causing abnormal spindle assembly.9 It has been reported that single-nucleotide polymorphisms (SNPs) in AURKA or AURKB are associated with the risk and survival of several cancers including breast cancer,14 esophageal cancer,15 and so on. But till now, there is no research about polymorphisms in AURKA or AURKB and prognosis of TNBC patients. In our study, we first demonstrated that polymorphisms in AURKA or AURKB gene were associated with the survival of TNBC patients.

Materials and methods

Study subjects

Between January 2004 and December 2012, 273 primary TNBC patients treated with taxane-based adjuvant chemotherapy were enrolled in this study. Blood samples were collected from each patient. Patients were followed up until July 30, 2017, to collect data on recurrence and death. The disease-free survival (DFS) time was defined as the time from the date of diagnosis until the date of first locoregional recurrence, first distant metastasis, or death from any cause (whichever came first). Overall survival (OS) was defined as the time from the date of diagnosis to the date of death from any reason or last follow-up. Formalin-fixed, paraffin-embedded breast cancer tissue samples were obtained from the patients. Immunohistochemistry (IHC) performed with anti-ER and anti-PR antibodies was used to evaluate the ER and PR status. A positive ER and PR status was defined by nuclear staining of more than 1% according to the guidelines issued by the American Society of Clinical Oncology (ASCO) and the College of American Pathologists (CAPs) in 2010.16 To determine the HER2 status, IHC or fluorescence in situ hybridization (FISH) was performed.17 Tumors negative for ER, PR, and HER2 were defined as TNBCs.

Ethics statement

This investigation was approved by the institutional review board of the Chinese Academy of Medical Sciences Cancer Hospital. It was conducted in accordance with the ethical standards of the Declaration of Helsinki and following the national and international guidelines. Written informed consent was obtained from all patients.

SNP selection and genotyping

Genotype data from AURKA and AURKB gene regions encompassing 10 kb of upstream and 3 kb of downstream flanking sequences were extracted from the HapMap Chinese Han population (Hapmap Data Rel 27, Phase II + III, http://www.HapMap.org). Haploview 4.2 software (http://www.broadinstitute.org/mpg/haploview) was used to identify Tag SNPs. The inclusion criteria were SNPs known in ethnic Han Chinese people and with a minor allele frequency (MAF) of 0.05. Finally, a total of 11 candidate SNPs were selected for genotyping, and information for these SNPs is listed in Table 1. Primers and probes were designed using MassARRAY Typer 4.0 software.
Table 1

Information for the SNPs genotyped in this study

SNPsPositionLocationAllelesGeneMAF in CHB
rs1048580520:56370727Intron variantA/GAURKA0.302
rs146805620:56390932Intron variantC/GAURKA0.128
rs223620720:56392509utr variant 5 primeA/GAURKA0.093
rs229801620:56384240Intron variantC/GAURKA0.367
rs609912820:56390288Intron variantG/TAURKA0.167
rs817320:56369735utr variant 3 primeC/GAURKA0.395
rs750335317:8204661Downstream variant 500BG/TAURKB0.163
rs1165199317:8212456Upstream variant 2 KBC/TAURKB0.105
rs1186991417:8211831Upstream variant 2 KBG/TAURKB0.386
rs228959017:8207446Intron variantA/CAURKB0.267
rs302725717:8208935Intron variantC/TAURKB0.267

Abbreviations: CHB, Han Chinese in Beijing; MAF, minor allele frequency; SNP, single-nucleotide polymorphism.

Peripheral blood samples (5 mL) were collected from each subject on recruitment. Genomic DNA was isolated by the routine phenol–chloroform method. Each DNA sample was diluted to a working concentration of 10 ng/mL for genotyping. Genotyping was conducted using the MassARRAY MALDI-TOF System (Sequenom Inc., San Diego, CA, USA)18,19 at once by the method described in the Sequenom Genotyping Protocol. Twenty percent duplicate samples and negative controls (without DNA) were included for quality assurance of genotyping. Concordance for duplicate samples was 100%. The analysts who carried out the genotyping were blinded to the group information on each sample.

Statistical analyses

SPSS version 18.0 (SPSS Inc, Chicago, IL, USA) was used for statistical analysis. The 5-year DFS rates and 5-year OS rates were estimated by the Kaplan–Meier product limit method for each of the different genotypes and expressed in percentages. Comparisons were made with the log-rank test. HRs of recurrence/metastasis and death with 95% CIs were estimated by using the Cox model. The multivariate analysis was adjusted for age (≤50 vs >50), histological grade (1–2 vs 3 vs unknown [UK]), tumor size (≤2 cm vs >2 cm), lymph node status (with vs without regional lymph node metastasis), and vascular invasion (with vs without vascular invasion). We performed subgroup analysis for polymorphisms, which were associated with OS or DFS of patients in multivariate analysis. Since there were only 10 patients with rs6099128 GG genotype, we did not perform subgroup analysis for rs6099128. All statistical tests were two sided, and P < 0.05 was considered significant.

Results

Clinical characteristics and survival of TNBC patients

A total of 273 patients were enrolled in this study. The median age at diagnosis is 48 years (range, 22–75 years). The 5-year OS rate was 87.1%, and the 5-year DFS rate was 72.8%. Among total patients, 142 (52.0%) and 131 (48.0%) patients were at pre- and post-menopausal stages, respectively. Seventy (25.6%) patients presented with grade 1–2 and 152 (55.7%) with grade 3 tumors. Eighty-four (30.8%), 137 (50.2%), and 52 (19.0%) subjects were diagnosed at stage I, II, and III, respectively. The relationship between clinicopathological characteristics and survival of these patients is summarized in Table 2. Patients with grade 1–2 tumors had a significantly higher 5-year OS rate than those with grade 3 tumors (96.8% vs 79.5%, P = 0.039, HR = 3.640, 95% CI = 1.071–12.373). Tumor size and lymph node status were significantly related to both DFS and OS. No significant association was observed between age or menopausal status and TNBC survival. After multivariate analysis, tumor size (P = 0.024, HR = 3.149, 95% CI = 1.166–8.509) and lymph node status (P < 0.001, HR = 11.058, 95% CI = 3.287–37.206) were demonstrated to be independent prognostic factors.
Table 2

Clinicopathological characteristics and survival of TNBC

VariablesPatients (%)5-year DFS (%)HR (95% CI)P5-year OS (%)HR (95% CI)P
Age (years)
≤50166 (60.8)68.91 (Ref)87.21 (Ref)
>50107 (39.2)79.50.586 (0.339–1.011)0.05586.80.876 (0.403–1.901)0.737
Menopause
Pre142 (52.0)72.11 (Ref)90.11 (Ref)
Post131 (48.0)72.91.320 (0.806–2.160)0.27083.81.271 (0.605–2.673)0.526
Grade
1–270 (25.6)68.91 (Ref)96.81 (Ref)
3152 (55.7)76.91.101 (0.609–1.992)0.75079.53.640 (1.071–12.373)0.039
UK51 (18.7)71.90.977 (0.469–2.034)0.95091.12.219 (0.554–8.891)0.260
Vascular invasion
Negative255 (93.4)73.51 (Ref)87.11 (Ref)
Positive18 (6.6)64.21.477 (0.636–3.427)0.36482.62.108 (0.729–6.097)0.169
Tumor size
≤2 cm127 (46.5)83.51 (Ref)95.61 (Ref)
>2 cm146 (53.5)63.92.376 (1.377–4.098)0.00280.33.983 (1.514–10.478)0.005
Lymph node
Negative162 (59.3)81.01 (Ref)98.11 (Ref)
Positive111 (40.7)61.03.039 (1.822–5.068)<0.00172.113.219 (3.990–43.797)<0.001
TNM
I84 (30.8)85.41 (Ref)100.01 (Ref)
II137 (50.2)75.61.814 (0.852–3.860)0.12292.95.801 (0.742–45.350)0.094
III52 (19.0)45.57.272 (3.419–15.468)<0.00152.336.227 (4.811–272.806)<0.001

Abbreviations: DFS, disease-free survival; OS, overall survival; Ref, reference; TNBC, triple-negative breast cancer; UK, unknown.

Polymorphisms in AURKA or AURKB gene and survival of TNBC patients

The results of relationship between polymorphisms in AURKA or AURKB and TNBC survival in different genetic models are summarized in Tables 3 and 4. In univariate analysis, AURKA rs10485805 GA genotype carriers had worse prognosis than GG genotype carriers (P = 0.043, HR = 2.177, 95% CI = 1.024–4.628). But after multivariate analysis, there was no association between rs10485805 genotype and OS. In multivariate analysis, AURKA rs6099128 GG genotype carriers had significantly worse OS than TT+ TG genotype carriers (P = 0.003, HR = 12.499, 95% CI = 2.357–66.298; Figure 1). Two polymorphisms in AURKB were significantly associated with DFS in both univariate and multivariate analyses, including AURKB rs11651993 and AURKB rs2289590 (Figures 2 and 3). AURKB rs11651993 TT genotype carriers had better DFS than TC + CC genotype carriers (P = 0.018, HR = 1.876, 95% CI = 1.116–3.154). AURKB rs2289590 CC genotype carriers had worse DFS than CA + AA genotype carriers (P = 0.021, HR = 0.536, 95% CI = 0.315–0.912).
Table 3

AURKA or AURKB genotypes and DFS

VariablesPatients (%)5-year DFS (%)Crude
Adjusted
HR (95% CI)PHR (95% CI)P
AURKB rs11651993
TT207 (75.8)76.21 (Ref)1 (Ref)
TC58 (21.3)64.01.876 (1.087–3.237)0.0241.838 (1.064–3.173)0.029
CC8 (2.9)56.32.417 (0.745–7.841)0.1422.162 (0.652–7.168)0.208
TT vs TC + CC1.934 (1.149–3.254)0.0131.876 (1.116–3.154)0.018
TT + TC vs CC2.045 (0.639–6.543)0.2281.868 (0.570–6.127)0.302
AURKB rs2289590
CC152 (55.7)68.11 (Ref)1 (Ref)
CA105 (38.5)77.00.562 (0.325–0.972)0.0390.533 (0.307–0.927)0.026
AA16 (5.8)87.50.357 (0.086–1.475)0.1550.559 (0.130–2.400)0.434
CC vs CA + AA0.531 (0.313–0.902)0.0190.536 (0.315–0.912)0.021
CC + CA vs AA0.438 (0.107–1.796)0.2520.685 (0.161–2.922)0.609

Abbreviations: DFS, disease-free survival; OS, overall survival; Ref, reference.

Table 4

AURKA or AURKB genotypes and overall survival

Variables5-year OS (%)Crude
Adjusted
HR (95% CI)PHR (95% CI)P
AURKA rs10485805
GG91.21 (Ref)1 (Ref)
GA78.92.177 (1.024–4.628)0.0431.987 (0.912–4.328)0.084
AA100.0
GG vs GA + AA1.757 (0.830–3.719)0.1411.605 (0.746–3.451)0.226
GG + GA vs AA0.043 (0.000–19.180)0.312
AURKA rs6099128
TT88.41 (Ref)1 (Ref)
TG85.51.081 (0.434–2.693)0.8681.128 (0.448–2.841)0.799
GG45.03.248 (0.749–14.091)0.11612.889 (2.386–69.627)0.003
TT vs TG + GG1.296 (0.570–2.945)0.5361.440 (0.627–3.308)0.391
TT + TG vs GG0.313 (0.073–1.339)0.11712.499 (2.357–66.298)0.003

Abbreviations: OS, overall survival; Ref, reference.

Figure 1

Kaplan–Meier curve of OS for patients with different AURKA rs6099128 genotypes.

Abbreviation: OS, overall survival.

Figure 2

Kaplan–Meier curve of DFS for patients with different AURKB rs11651993 genotypes.

Abbreviation: DFS, disease-free survival.

Figure 3

Kaplan–Meier curve of DFS for patients with different AURKB rs2289590 genotypes.

Abbreviation: DFS, disease-free survival.

Polymorphisms in AURKA or AURKB gene and survival of TNBC in different subgroups

In multivariate analysis, AURKA rs6099128 was associated with OS, but since there were only 10 patients with GG genotype, we did not explore the relationship in subgroups. As shown in Table 5, we explored the relationship between AURKB rs11651993 or rs2289590 and survival of TNBC in different subgroups. AURKB rs11651993 TC + CC genotype predicted worse DFS in subgroups of age ≤ 50 years, post-menopausal, grade UK, tumor size >2 cm, and lymph node negative. It also predicted shorter OS in subgroups of age > 50 years and grade 3. AURKB rs2289590 CA + AA genotype could predict favorable DFS in pre-menopausal, grade 3, and lymph node-positive patients. No significant relationship was observed between rs2289590 and OS in any subgroups.
Table 5

Subgroup analysis of polymorphisms and survival

VariantsSubgroupDFS
OS
HR (95% CI)PHR (95% CI)P
RS11651993TT vs TC + CCAge ≤ 50 years1.942 (1.046–3.606)0.0361.093 (0.358–3.333)0.876
Age > 50 years1.913 (0.738–4.956)0.1827.309 (1.817–29.402)0.005
Pre-menopausal1.314 (0.581–2.975)0.5122.598 (0.842–8.015)0.097
Post-menopausal2.613 (1.309–5.218)0.0061.806 (0.612–5.328)0.284
Grade 1–21.274 (0.442–3.671)0.6540.033 (0.000–4,638.821)0.572
Grade 31.769 (0.864–3.623)0.1192.801 (1.086–7.224)0.033
Grade UK3.480 (1.110–10.914)0.0324.420 (0.810–24.130)0.086
Tumor size ≤2 cm1.844 (0.681–4.991)0.2281.149 (0.119–11.093)0.904
Tumor size >2 cm1.990 (1.080–3.668)0.0272.236 (0.966–5.178)0.060
LN negative3.520 (1.526–8.122)0.0032.525 (0.210–30.414)0.466
LN positive1.377 (0.689–2.751)0.3652.198 (0.965–5.006)0.061
RS2289590CC vs CA + AAAge ≤ 50 years0.618 (0.337–1.135)0.1211.228 (0.487–3.095)0.663
Age > 50 years0.343 (0.113–1.042)0.0591.229 (0.354–4.273)0.745
Pre-menopausal0.377 (0.161–0.884)0.0250.978 (0.325–2.944)0.968
Post-menopausal0.676 (0.341–1.343)0.2641.405 (0.509–3.878)0.512
Grade 1–20.528 (0.183–1.521)0.2371.730 (0.144–20.752)0.665
Grade 30.358 (0.162–0.789)0.0110.780 (0.306–1.989)0.602
Grade UK1.437 (0.481–4.293)0.5165.701 (0.661–49.170)0.113
Tumor size ≤2 cm0.471 (0.168–1.322)0.1532.041 (0.340–12.239)0.435
Tumor size >2 cm0.543 (0.293–1.006)0.0521.084 (0.478–2.461)0.847
LN negative0.549 (0.226–1.334)0.18595.034 (0.007–1280606)0.348
LN positive0.507 (0.262–0.983)0.0440.858 (0.388–1.896)0.705

Abbreviations: DFS, disease-free survival; OS, overall survival; Ref, reference; UK, unknown.

Discussion

Polymorphisms in AURKA or AURKB have been reported to be associated with prognosis of some kinds of cancers. Up to now, there is no such comprehensive research that investigated the association between polymorphisms in both AURKA and AURKB and the outcome of TNBC patients. In our study, we first demonstrated that AURKA rs6099128 GG genotype carriers had significantly worse OS than TT + TG genotype carriers, AURKB rs11651993 C allele was associated with worse DFS, and AURKB rs2289590 A allele was significantly associated with better DFS. AURKA gene is an oncogene located on chromosome 20q13. Polymorphisms in AURKA gene are associated with risk and intrinsic subtype of breast cancer.20,21 In the study by Ruan et al,22 AURKA rs10485805 was associated with risk of breast cancer under the recessive genetic model (OR = 0.38, 95% CI = 0.18–0.82, P = 0.014); but there is no relationship between rs2298016 and risk in Chinese population. Taylor et al23 found that rs6099128 had reduced ORs for luminal A (OR = 0.76, 95% CI = 0.60–0.95) and basal-like breast cancer (OR = 0.54, 95% CI = 0.37–0.80). Only a few studies in the literature reported the association between polymorphisms in AURKA and OS of breast cancer. Shi et al24 found that in the Swedish population, for rs8173, the BC-specific survival was worse in women with at least one G allele, when they had tumors smaller than 2 cm (HR = 2.74, 95% CI = 1.08–6.98) or stage 0–I tumors (HR = 6.94, 95% CI = 1.45–33.22). However, in our research, there is no relationship between genotypes of rs8173 and survival of TNBC. Maybe it is because of the different ethnic groups and different subtypes of BC. Among the six SNPs of AURKA investigated in our study, rs1468056 and rs2236207 had never been reported. We found that they were not associated with OS of TNBC. We first demonstrated that AURKA rs6099128 GG genotype carriers had significantly worse OS than TT + TG genotype carriers (P = 0.003, HR = 12.499, 95% CI = 2.357–66.298). High AURKA expression was strongly associated with decreased survival of breast cancer (P = 0.0005), and it was an independent prognostic marker in the study by Nadler et al.25 In TNBC patients with AURKA high expression, the risk of distant recurrence peaked at the first 3 years and declined rapidly thereafter, whereas patients with AURKA low expression showed a relatively constant risk of recurrence during the entire follow-up period. Univariate and multivariate analysis showed that overexpression of AURKA predicted poor OS (P = 0.002) and progression-free survival (P = 0.012) in TNBC.26 AURKA had been reported to interact and phosphorylate several important proteins involved in stress response and cell cycle checkpoint after DNA damage.27 Overexpression of AURKA led to diminished transcriptional activity and increased degradation of p53, causing checkpoint defects and genetic instability and ultimately facilitating cancer development and progression.28 AURKB gene is located on chromosome 17p13. In German population,29 synonymous AURKB rs2241909 (885A>G) polymorphism resulted in an increased familial breast cancer risk for carriers of the homozygous 885G genotype (OR = 1.45, 95% CI = 1.05–2.0, P = 0.02). There have been debating data regarding the role of the AURKB expression in cancer prognosis. Zhang et al30 found that AURKB expression was correlated with the proliferation index (P < 0.001) and p53 expression (P = 0.014) in breast cancer tissues. Higher expression of AURKB is significantly correlated with the poor survival in these cases (P = 0.038). A multivariate Cox regression analysis demonstrated that AURKB expression is an independent prognostic indicator of breast cancer DFS (HR = 1.39, 95% CI = 1.04–1.86). While in the study by Nadler et al,25 AURKB expression was not associated with the survival of breast cancer patients. None of the polymorphisms in AURKB of our study has been reported in TNBC. We first found that rs11651993 TC + CC genotype predicted worse DFS in subgroup of age ≤ 50 years, post-menopausal, grade UK, tumor size >2 cm, and lymph node negative. It also predicted shorter OS in subgroup of age > 50 years and grade 3. Rs2289590 CA + AA genotype could predict favorable DFS in pre-menopausal, grade 3, and lymph node-positive patients. All patients in our study received taxane-based adjuvant chemotherapy. Taxanes are microtubule targeting agents (MTAs), which are most widely used drugs in adjuvant setting for TNBC patients. The cytotoxic action of these compounds is mediated primarily through their binding of β-tubulin monomers, leading to microtubule stabilization, thus blocking their depolymerization and subsequently triggering cell cycle arrest at the G2/M phase.31 Considering the role of Aurora kinases in spindle formation and the reported extent of their deregulation in cancer, we hypothesize that polymorphisms in AURKA or AURKB might contribute to taxane resistance and then influence the survival of cancer patients. Zhang et al30 demonstrated that in breast cancer patients who received neoadjuvant chemotherapy (containing sequential taxane and anthracycline-based regimens), elevated expression of AURKB contributed to chemoresistance (P = 0.011). In taxane-resistance breast cancer cell lines, expression of AURKA was significantly higher. Knockdown of AURKA not only markedly decreased the expression of P-gp but also downregulated the P-gp function in resistant breast cancer cells. The results indicated that AURKA plays a crucial role in paclitaxel-resistant breast cancer.32 However, the underlying mechanisms of these SNPs on survival of TNBC are not yet clear and need to be further investigated. By silico analysis of prediction of binding motifs, Mesic et al33 indicated that polymorphic sites in AURKA and AURKB could bind different transcription factors. As for AURKA rs8173, when the G allele was present, C/EBPalpha, C/EBPbeta, and NF-1 transcription factor binding motifs were recognized, whereas when the same region contained the C allele, additional E2F and RAR-β transcription factor motifs were identified. In the case of AURKB rs2289590, when the A allele was present, PEA3 and TFII-I binding motifs were recognized. In contrast, when the C allele is present, PEA3, TFII-I, and YY1 binding motifs were identified. Since YY1 expression level and/or activity is associated with unchecked cell proliferation, resistance to apoptosis, metastasis, and tumor cell resistance to chemotherapeutics,34 the binding of an additional YY1 protein in the presence of C allele may alter the level of AURKB expression and then influence the survival, which might be a possible explanation for our result that AURKB rs2289590 A allele was significantly associated with better DFS. Previous studies enrolled different subtypes of breast cancer patients, and the regimens are not consistent. In our study, only TNBC patients were enrolled, which can better explain the correlation between polymorphisms in AURKA or AURKB and survival. There are some limitations of our study. First, this was a retrospective study, so selection bias might exist. Second, the sample size was relatively small, and the prospective large-scale studies are needed to confirm the conclusions. Finally, since we did not explore the mechanisms, further studies on the biological mechanisms are warranted.

Conclusion

For the first time in TNBC patients receiving taxane-based adjuvant chemotherapy, we demonstrated that AURKA rs6099128, AURKB rs11651993, and AURKB rs2289590 were associated with the survival. Since most polymorphisms have never been reported, more research are needed to verify our results.
  34 in total

1.  Antitumor activity and safety profile of weekly carboplatin plus paclitaxel in metastatic breast cancer: a ten-year, monocentric, retrospective study.

Authors:  Claudio Vernieri; Monica Milano; Alessia Mennitto; Claudia Maggi; Benvenuto Ferrari; Lucia Rinaldi; Roberta Mennitto; Claudia Stefanetti; Barbara Re; Gabriella Mariani; Giulia Bianchi; Giuseppe Capri; Filippo de Braud
Journal:  Breast Cancer Res Treat       Date:  2017-06-14       Impact factor: 4.872

2.  Aurora kinase A is essential for correct chromosome segregation in mouse zygote.

Authors:  Veronika Kovarikova; Jan Burkus; Pavol Rehak; Adela Brzakova; Petr Solc; Vladimir Baran
Journal:  Zygote       Date:  2015-07-15       Impact factor: 1.442

3.  Association of Aurora-A (STK15) kinase polymorphisms with clinical outcome of esophageal cancer treated with preoperative chemoradiation.

Authors:  Jennifer Y Pan; Jaffer A Ajani; Jian Gu; Yubo Gong; Angel Qin; Angel Quin; Maosheng Hung; Xifeng Wu; Julie G Izzo
Journal:  Cancer       Date:  2011-12-27       Impact factor: 6.860

4.  Elevated Aurora B expression contributes to chemoresistance and poor prognosis in breast cancer.

Authors:  Yiqian Zhang; Chunling Jiang; Huilan Li; Feng Lv; Xiaoyan Li; Xiaolong Qian; Li Fu; Bo Xu; Xiaojing Guo
Journal:  Int J Clin Exp Pathol       Date:  2015-01-01

5.  Paclitaxel resistance in non-small-cell lung cancer associated with beta-tubulin gene mutations.

Authors:  M Monzó; R Rosell; J J Sánchez; J S Lee; A O'Brate; J L González-Larriba; V Alberola; J C Lorenzo; L Núñez; J Y Ro; C Martín
Journal:  J Clin Oncol       Date:  1999-06       Impact factor: 44.544

6.  Genetic polymorphisms in AURKA and BRCA1 are associated with breast cancer susceptibility in a Chinese Han population.

Authors:  Yuan Ruan; Ai-Ping Song; Hui Wang; Yun-Tao Xie; Ji-Yuan Han; Constantin Sajdik; Xin-Xia Tian; Wei-Gang Fang
Journal:  J Pathol       Date:  2011-05-19       Impact factor: 7.996

7.  Cancer Statistics, 2017.

Authors:  Rebecca L Siegel; Kimberly D Miller; Ahmedin Jemal
Journal:  CA Cancer J Clin       Date:  2017-01-05       Impact factor: 508.702

8.  Expression of Aurora A (but not Aurora B) is predictive of survival in breast cancer.

Authors:  Yasmine Nadler; Robert L Camp; Candice Schwartz; David L Rimm; Harriet M Kluger; Yuval Kluger
Journal:  Clin Cancer Res       Date:  2008-07-15       Impact factor: 12.531

9.  INCENP-aurora B interactions modulate kinase activity and chromosome passenger complex localization.

Authors:  Zhenjie Xu; Hiromi Ogawa; Paola Vagnarelli; Jan H Bergmann; Damien F Hudson; Sandrine Ruchaud; Tatsuo Fukagawa; William C Earnshaw; Kumiko Samejima
Journal:  J Cell Biol       Date:  2009-11-30       Impact factor: 10.539

Review 10.  Role of Platinum in Early-Stage Triple-Negative Breast Cancer.

Authors:  Alyssa La Belle; Jude Khatib; William P Schiemann; Shaveta Vinayak
Journal:  Curr Treat Options Oncol       Date:  2017-11-06
View more
  9 in total

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

Authors:  Endah Endah; Febri Wulandari; Yurananda Putri; Riris Istighfari Jenie; Edy Meiyanto
Journal:  Iran J Pharm Res       Date:  2022-02-04       Impact factor: 1.962

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

Authors:  Pei-Ju Wu; Chun-Hao Wang; Ming-Hong Hsieh; Chung-Yuan Lee; Po-Hui Wang; Chiao-Wen Lin; Shun-Fa Yang; Maw-Sheng Lee
Journal:  Int J Med Sci       Date:  2021-04-22       Impact factor: 3.738

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

Authors:  Junhan Jiang; Zihe Guo; Junnan Xu; Tao Sun; Xinyu Zheng
Journal:  Onco Targets Ther       Date:  2020-06-03       Impact factor: 4.147

4.  AURKB: a promising biomarker in clear cell renal cell carcinoma.

Authors:  Bangbei Wan; Yuan Huang; Bo Liu; Likui Lu; Cai Lv
Journal:  PeerJ       Date:  2019-09-16       Impact factor: 2.984

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

Authors:  Na Yang; Chang Wang; Jian Wang; Zifeng Wang; Di Huang; Min Yan; Muhammad Kamran; Quentin Liu; BangLao Xu
Journal:  J Cell Mol Med       Date:  2019-07-30       Impact factor: 5.310

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

Authors:  Arjun Bhattacharya; Montserrat García-Closas; Andrew F Olshan; Charles M Perou; Melissa A Troester; Michael I Love
Journal:  Genome Biol       Date:  2020-02-20       Impact factor: 13.583

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

Authors:  Maiquidieli Dal Berto; Giovana Tavares Dos Santos; Aniúsca Vieira Dos Santos; Andrew Oliveira Silva; José Eduardo Vargas; Rafael José Vargas Alves; Fernanda Barbisan; Ivana Beatrice Mânica da Cruz; Claudia Giuliano Bica
Journal:  Discov Oncol       Date:  2021-10-01

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

Authors:  Yun Fu; Qu-Zhi Zhou; Xiao-Lei Zhang; Zhen-Zhen Wang; Peng Wang
Journal:  Med Sci Monit       Date:  2019-11-23

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

Authors:  Kun Wang; Yue Zhang; Xiaodan Yang; Tingsong Chen; Tao Han
Journal:  Transl Cancer Res       Date:  2020-08       Impact factor: 1.241

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.