Literature DB >> 23652306

Expression of steroid receptor coactivator 3 in ovarian epithelial cancer is a poor prognostic factor and a marker for platinum resistance.

C Palmieri1, O Gojis, B Rudraraju, C Stamp-Vincent, D Wilson, S Langdon, C Gourley, D Faratian.   

Abstract

BACKGROUND: Steroid receptor coactivator 3 (SRC3) is an important coactivator of a number of transcription factors and is associated with a poor outcome in numerous tumours. Steroid receptor coactivator 3 is amplified in 25% of epithelial ovarian cancers (EOCs) and its expression is higher in EOCs compared with non-malignant tissue. No data is currently available with regard to the expression of SRC-3 in EOC and its influence on outcome or the efficacy of treatment.
METHODS: Immunohistochemistry was performed for SRC3, oestrogen receptor-α, HER2, PAX2 and PAR6, and protein expression was quantified using automated quantitative immunofluorescence (AQUA) in 471 EOCs treated between 1991 and 2006 with cytoreductive surgery followed by first-line treatment platinum-based therapy, with or without a taxane.
RESULTS: Steroid receptor coactivator 3 expression was significantly associated with advanced stage and was an independent prognostic marker. High expression of SRC3 identified patients who have a significantly poorer survival with single-agent carboplatin chemotherapy, while with carboplatin/paclitaxel treatment such a difference was not seen.
CONCLUSION: Steroid receptor coactivator 3 is a poor prognostic factor in EOCs and appears to identify a population of patients who would benefit from the addition of taxanes to their chemotherapy regimen, due to intrinsic resistance to platinum therapy.

Entities:  

Mesh:

Substances:

Year:  2013        PMID: 23652306      PMCID: PMC3670494          DOI: 10.1038/bjc.2013.199

Source DB:  PubMed          Journal:  Br J Cancer        ISSN: 0007-0920            Impact factor:   7.640


Ovarian cancer is the second most common gynaecological cancer but the most lethal, with over 200 000 cases diagnosed and 140 000 deaths worldwide per year (Ferlay ), and in the majority of cases presents with disease that has spread beyond the pelvis. Surgical debulking and systemic chemotherapy with platinum/taxanes are the mainstays of treatment, and despite treatment advances the 5-year survival remains poor. There is good evidence that platinum–taxane first-line chemotherapy is superior to other chemotherapy regimens for ovarian cancer (Thigpen ), but 20–30% of patients do not respond to this therapy. Experimental models of ovarian cancer have demonstrated that expression of the oestrogen receptor-α (ERα) is associated with a growth response to oestrogen, and in these models growth inhibition occurs with anti-oestrogen both in vitro and in vivo (Langdon , 1993, 1994a, 1994b). In addition, within this context oestrogen was shown to regulate a number of known ER-regulated genes (Langdon , 1994b, 1998). Studies have subsequently utilised endocrine therapy in the clinical setting in the form of the selective oestrogen receptor modulator tamoxifen or inhibition of aromatase. Response rates of 13–17% have been reported in ovarian cancer with tamoxifen (Hatch ; Ahlgren ; Markman ), while with aromatase inhibitors radiological response rates of 0–15% and marker response in 9–15% have been documented (Bowman ; del Carmen ; Papadimitriou ). Benefit to treatment has been linked to a higher expression of ER (Bowman ), and a subsequent study, which selected ovarian cancers based on an ER histoscore of >150, found a higher marker and radiological response rate with letrozole in these cases as compared with previous studies (Smyth ). Furthermore, similar to breast cancer HER2 is lower in endocrine-responsive ovarian tumours (Bowman ; Smyth ). Co-activators are essential for the transcriptional activation of ligand-bound ER, and one such important cofactor is steroid receptor coactivator 3 (SRC3), a member of the p160 steroid receptor coactivator (SRC) family. Steroid receptor coactivator 3 has been showed to be amplified as well as have elevated expression in malignant tissue as compared with normal tissue (Gojis , 2010b). It also has been shown to correlate with markers of aggressive disease, such as increased Ki-67, larger tumours, lymph node involvement, as well as being associated with a poorer prognosis (Gojis , 2010b) and resistance to endocrine resistance in breast cancer (Gojis ). Within the context of breast cancer, chromatin immunoprecipitation-based assays have shown that PARD6B/PAR6 and FER1L3 may be regulated by SRC3 via ER (Labhart ). In addition, SRC3 can compete with PAX2 for binding to the HER2 cis-regulatory element, with a resultant increase in HER2 transcription and cell proliferation (Hurtado ). In sporadic ovarian cancer, amplification of SRC3 occurs in 25% of cases, with none seen in familial cases (Tanner). Amplification of SRC3 is associated with ER positivity and a poorer overall survival (Tanner). In addition, the length of the polyQ region within SRC3 has been associated with time to disease recurrence and overall survival, with a short SRC-3 polyQ genotype (<28 repeats) associated with reduced time to both these events (Li ). These data suggest a role for SRC3 in the pathogenesis of sporadic ovarian carcinoma and a possible effect on survival. To date, the expression of SRC3 and its effect on outcome and response to treatment have yet to be explored in ovarian cancer. In this study, the expression of SRC3 in a cohort of ovarian cancers was undertaken and its effect on outcome and response to treatment investigated. In addition, the expression of ERα, HER2, PAX2 and PAR6 were assessed.

Patients and Methods

Patients

The study was approved by the Lothian Research Ethics Committee (08/S1101/41). No informed consent (written or verbal) was obtained for use of retrospective tissue samples from the patients within this study, most of whom were deceased, as this was not deemed necessary by the Ethics Committee. The study population consisted of 471 FFPE ovarian tumours treated in the Edinburgh Cancer Centre between 1991 and 2006, as described previously (Faratian , 2011b ). Summary patient characteristics are shown in Table 1. Standard treatment included cytoreductive surgery followed by platinum-based therapy, with or without combination with a taxane.
Table 1

Clinicopathologic features of patients and first-line treatment received for ovarian cancer

CharacteristicNo.PercentPrognostic significance P-value
Number of patients
471
100
 
Age  0.059
Median age60.4  
Age range
27–86
 
 
First-line chemotherapy regimen
 
 
0.04
Platinum-based28360.1 
Platinum and taxane17537.2 
Other/none112.3 
Unknown
2
0.4
 
Stage
 
 
<0.0001
I4710.0 
II5611.9 
III27157.5 
IV7816.6 
Unknown
19
4.0
 
Histology
 
 
<0.0001
Serous26456.1 
Clear cell245.1 
Endometrioid9420 
Mixed6113 
MMMT00 
Mucinous143.0 
Other122.5 

Abbreviation: MMMT=malignant mixed mesodermal tumor

Outcome

Overall survival was calculated from the date of diagnosis (primary surgery) to the date of death by ovarian cancer, or to the date of last follow-up (censored). Patients who died from disease other than ovarian cancer were censored. Tumours were taken from primary site (not metastatic) and before commencement of chemotherapy.

Immunohistochemistry

Two tissue microarrays (TMAs) containing 0.6-mm cores of tumours were constructed using a previously described methodology (Graham ). Two tissue microarrays were manually stained in triplicate utilising SRC3, ERα, HER2, PAX2 and PAR6 primary antibodies as detailed in Table 2. All TMA tissue sections were incubated with the primary antibodies for 1 h at room temperature. Protein expression was quantified using AQUA. Immunofluorescence for protein targets was performed using methods described previously (Faratian ,2011b). Pan-cytokeratin antibody was used to identify infiltrating tumour cells, DAPI counterstain to identify nuclei and Cy-5-tyramide detection for target for compartmentalised (tissue and subcellular) analysis of tissue sections. Monochromatic images of each TMA core were captured at × 20 objective using an Olympus AX-51 epifluorescence microscope (Tokyo, Japan), and high-resolution digital images were analysed by the AQUAnalysis software (HistoRx, Branford, CN, USA). If the tumour epithelium comprised <5% of total core area, the core was excluded from analysis, to ensure adequate representation of tissue.
Table 2

Primary antibodies used in this study

Primary antibodyManufacturerCatalogue numberConcentration
SRC3
BD Transduction Laboratories
61105
1 : 50
ERα
Neomarkers
RM-9101-S1
1 : 50
HER2
Dako
A0485
1 : 400
PAX2
Abcam
23799
1 : 400
PAR6Abcam578381 : 100

Abbreviations: ERα=oestrogen receptor-α SRC3=steroid receptor coactivator 3.

Statistical analyses

Overall survival was assessed by Kaplan–Meier analysis with log-rank testing to determine statistical significance. Univariate and multivariate analyses were performed using Cox proportional hazards regression models. Comparison of differences in means was performed using the Kruskal–Wallis test. To determine the cut-point value for each of the phosphoproteins for Kaplan–Meier analysis, we utilised X-Tile, which allows determination of an optimal cut-point while correcting for the use of minimum P statistics, as described previously (Camp ). Two methods of statistical correction for the use of minimal P approach were used, the first calculation of a Monte Carlo P-value, and for the second, the Miller–Siegmund minimal P correction (Altman ). All calculations and analyses were two-tailed, where appropriate, and were carried out with SPSS 14.0 for Windows (SPSS Inc., Chicago, IL, USA).

Results

Patient characteristics

Patient characteristics for the population are summarised in Table 1. The median age for the cohort was 60.4 years (range, 27–86 years); 57.5% (271 out of 471) had stage III tumours and 56% (264 out of 471) had serous type tumours. With regard to first-line treatment, 60% (283 out of 471) received platinum-based treatment, and 37% (175 out of 241) a platinum-taxane doublet.

Correlation of SRC3 with clinicopathological features and other biological parameters

With respect to histopathological parameters, SRC3 expression was significantly higher in stage III and stage IV tumours (Kruskal–Wallis test, P<0.001) and lower in endometrioid carcinomas when compared with other histological subtypes (Kruskal–Wallis test, P<0.001). Oestrogen receptor was significantly higher in stages III and IV (P=0.031), and lower in clear-cell carcinomas (Kruskal–Wallis test, P<0.0001); and HER2 was significantly higher in clear-cell and mixed cancers (Kruskal–Wallis test, P=0.025). Weak but significant correlations were seen between SRC3 and ERα, HER-2, PAX-2 and PAR6 (Figure 1 and Table 3).
Figure 1

Ovarian tumour core stained for SRC3: red=SRC3; green=cytokeratin; blue=nuclei; combined image=lower right.

Table 3

Correlation between protein concentrations of ER, HER-2, SRC-3, PAX-2 and PAR6

 
ERα
HER-2
SRC3
PAX-2
PAR6
 Correlation coefficientSignificanceCorrelation coefficientSignificanceCorrelation coefficientSignificanceCorrelation coefficientSignificanceCorrelation coefficientSignificance
ERα
1.000

−0.079
0.09
0.219
<0.001
0.200
<0.001
0.157
<0.001
HER-2
−0.079
0.090
1.000

0.190
<0.001
0.172
<0.001
0.159
0.001
SRC3
0.219
<0.001
0.190
<0.001
1.000

0.249
<0.001
0.127
0.008
PAX-2
0.200
<0.001
0.172
<0.001
0.249
<0.001
1.000

0.382
<0.001
PAR60.1570.0010.159<0.0010.1270.0080.382<0.0011.000

Abbreviations: ERα=oestrogen receptor-α; SRC3=steroid receptor co-activator 3.

SRC3 and outcome

High expression of SRC3 (as assessed by AQUA) identified patients who have a significantly worse overall survival (Figure 2; P-value⩽0.001, Miller–Siegmund P-value=0.0029, Monte-Carlo P-value <0.0001). With multivariate analysis, we identified ERα and SRC3 expressions as independent prognostic factors. Stage (P<0.001, relative risk=1.865), ER expression (P<0.001, relative risk=0.500), SRC3 expression (P=0.015, relative risk=1.349) and treatment regimen (P=0.025, relative risk=0.783).
Figure 2

Overall survival based on the expression of SRC3. The colour reproduction of this figure is available on the British Journal of Cancer journal online.

Expression of SRC3 and outcome of first-line chemotherapy

Expression of SRC3 identified patients who have a significantly improved survival when treated with single-agent carboplatin chemotherapy (P<0.001) (Figure 3a), with patients with low SRC3 having a better survival when treated with single carboplatin as compared to those with a high expression. In patients treated with the combination of carboplatin and paclitaxel, this difference is no longer seen in patients with low and high expression having a similar outcome (Figure 3b).
Figure 3

Overall survival based on the expression of SRC3 based on first-line therapy. (A) Single-agent platinum treatment and (B) platinum and taxane doublet.

Discussion

This is the first time that data relating to the expression of SRC3 in the context of ovarian cancer and its potential as a prognostic and treatment-predictive marker have been explored. As in other tumour types, high expression of SRC3 was associated with more advanced tumours (Gojis , 2010b), and the significant association with stage of disease is in keeping with the known role of SRC3 in cell motility and invasion (Bai ; Li , 2008b), which is known to involve focal adhesion turnover and focal adhesion kinase activation (Qin ), as well as upregulation of the expression of matrix metalloproteinase (Qin ). The role of SRC3 as a predictive factor in the response to oncological therapies has been previously explored in the context of endocrine therapy (particularly tamoxifen in breast cancer), but no previous reports have explored its importance in systemic cytotoxic treatments. With regard to tamoxifen and breast cancers, differing results have been reported with reference to SRC3 and its predictive nature. In a retrospective series of breast cancers, high SRC3 in the presence of tamoxifen was a negative prognostic factor (Osborne ). However, other retrospective series have found it associated with recurrence on tamoxifen but not with long-term outcome (Dihge ) or its expression alone had no influence on disease-free survival in tamoxifen-treated patients (Kirkgaard . In the context of premenopausal women, who entered into a randomised study of tamoxifen vs no tamoxifen, high SRC3 in the presence of tamoxifen treatment was associated with a significantly better disease-free survival (Alkner ). The reasons for these disparate results are likely to be related to patient heterogeneity as well as methodological issues. In the current cohort, high SRC3 was associated with a significantly poorer overall survival when single-agent carboplatin was utilised as first-line therapy compared to those with low SRC3. In those patients receiving the doublet carboplatin/paclitaxel, there was no difference in outcome based on SRC3 expression. These data would suggest that SRC3 is a potential marker for resistance to single-agent platinum therapy and could be used to identify cases of ovarian cancer that could benefit from carboplatin/paclitaxel combination therapy. The underlying mechanism for the involvement of SRC3 in resistance to single-agent platinum could be via its effect on insulin-like growth factor (IGF) signalling. It has been previously shown that increased IGF-1R mRNA expression is linked with resistance to cisplatin, and IGF-1R mRNA expression has been found to be strongly correlated with intrinsic cisplatin resistance status in a panel of human ovarian cancer cells (Eckstein ). Steroid receptor coactivator 3 is known to maintain IGF-I in the circulation (Liao ), and in the context of human breast cancer mediates the effects of IGF-1-induced proliferation, signalling and cell survival (Oh ). Furthermore, SRC3 is known to be phosphorylated by IGF-1 at tyrosine 1357, which contributes to it oncogenic behaviour (Oh ). Therefore, it could be hypothesised that the effects of SRC-3 seen in this report are mediated in an IGF-1/IGFR-dependent manner. A number of large randomised studies have explored the efficacy of paclitaxel in combination with platinum against a platinum-based control treatment as first-line treatment for ovarian cancer. However, only the third International Collaborative Ovarian Neoplasm study (ICON 3) (ICON, 2002) and Gynecology Oncology Group-132 (GOG-132) (Muggia ) included a randomisation to platinum alone, and in these studies the outcome with paclitaxel/platinum doublet was equivalent to platinum alone. Given the data presented here, it would be of interest to explore the expression of SRC3 and its influence on outcome in cases entered into ICON3 and GOG-132 to confirm its potential usefulness as a potential biomarker for treatment selection. This study, although it is based on a well-defined and large cohort of 471 patients, which were carefully followed up, is limited by the fact that it is a single-centre retrospective study. Furthermore, given we were unable to explore the potential efficacy of taxane alone. Therefore, these findings need to be explored in the context of ICON 3 (ICON, 2002) and GOG-132 (Muggia ). In summary, SRC3 is a poor prognostic factor in ovarian epithelial cancers and appears to identify patients who would benefit from the addition of taxanes to their platinum-based first-line treatment. Further studies of prospective randomised studies are required.
  37 in total

1.  Responsiveness of patients with advanced ovarian carcinoma to tamoxifen. A Gynecologic Oncology Group study of second-line therapy in 105 patients.

Authors:  K D Hatch; J B Beecham; J A Blessing; W T Creasman
Journal:  Cancer       Date:  1991-07-15       Impact factor: 6.860

2.  Tamoxifen in platinum-refractory ovarian cancer: a Gynecologic Oncology Group Ancillary Report.

Authors:  M Markman; K A Iseminger; K D Hatch; W T Creasman; W Barnes; B Dubeshter
Journal:  Gynecol Oncol       Date:  1996-07       Impact factor: 5.482

3.  AIB1 polymorphisms predict aggressive ovarian cancer phenotype.

Authors:  Andrew J Li; Dimitry L Lerner; Maria-Emily R Gapuzan; Beth Y Karlan
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2005-12       Impact factor: 4.254

Review 4.  First-line therapy in ovarian cancer trials.

Authors:  Tate Thigpen; Andreas duBois; Jessica McAlpine; Philip DiSaia; Keiichi Fujiwara; William Hoskins; Gunnar Kristensen; Robert Mannel; Maurie Markman; Jacobus Pfisterer; Michael Quinn; Nick Reed; Ann Marie Swart; Jonathan Berek; Nicoletta Colombo; Gilles Freyer; Dolores Gallardo; Marie Plante; Andres Poveda; Lawrence Rubinstein; Monica Bacon; Henry Kitchener; Gavin C E Stuart
Journal:  Int J Gynecol Cancer       Date:  2011-05       Impact factor: 3.437

5.  Paclitaxel plus carboplatin versus standard chemotherapy with either single-agent carboplatin or cyclophosphamide, doxorubicin, and cisplatin in women with ovarian cancer: the ICON3 randomised trial.

Authors: 
Journal:  Lancet       Date:  2002-08-17       Impact factor: 79.321

6.  Hormonal palliation of chemoresistant ovarian cancer: three consecutive phase II trials of the Mid-Atlantic Oncology Program.

Authors:  J D Ahlgren; N M Ellison; R J Gottlieb; F Laluna; J J Lokich; P R Sinclair; W Ueno; G L Wampler; K Y Yeung; D Alt
Journal:  J Clin Oncol       Date:  1993-10       Impact factor: 44.544

7.  Growth inhibition of oestrogen receptor-positive human ovarian carcinoma by anti-oestrogens in vitro and in a xenograft model.

Authors:  S P Langdon; A J Crew; A A Ritchie; M Muir; A Wakeling; J F Smyth; W R Miller
Journal:  Eur J Cancer       Date:  1994       Impact factor: 9.162

8.  Phase II trial of anastrozole in women with asymptomatic müllerian cancer.

Authors:  Marcela G del Carmen; Arlan F Fuller; Ursula Matulonis; Nora K Horick; Annekathryn Goodman; Linda R Duska; Richard Penson; Susana Campos; Maria Roche; Michael V Seiden
Journal:  Gynecol Oncol       Date:  2003-12       Impact factor: 5.482

9.  Tissue microarray technology in the routine assessment of HER-2 status in invasive breast cancer: a prospective study of the use of immunohistochemistry and fluorescence in situ hybridization.

Authors:  A D Graham; D Faratian; F Rae; J St J Thomas
Journal:  Histopathology       Date:  2008-06       Impact factor: 5.087

10.  The nuclear receptor coactivator AIB1 mediates insulin-like growth factor I-induced phenotypic changes in human breast cancer cells.

Authors:  Annabell Oh; Heinz-Joachim List; Ronald Reiter; Aparna Mani; Ying Zhang; Edmund Gehan; Anton Wellstein; Anna T Riegel
Journal:  Cancer Res       Date:  2004-11-15       Impact factor: 12.701

View more
  12 in total

Review 1.  Prognostic biomarkers in endometrial and ovarian carcinoma.

Authors:  Xavier Matias-Guiu; Ben Davidson
Journal:  Virchows Arch       Date:  2014-02-07       Impact factor: 4.064

Review 2.  SRC-3, a Steroid Receptor Coactivator: Implication in Cancer.

Authors:  Licen Li; Chu-Xia Deng; Qiang Chen
Journal:  Int J Mol Sci       Date:  2021-04-30       Impact factor: 5.923

3.  Steroid Receptor Coactivator-3 (SRC-3/AIB1) as a Novel Therapeutic Target in Triple Negative Breast Cancer and Its Inhibition with a Phospho-Bufalin Prodrug.

Authors:  Xianzhou Song; Chengwei Zhang; Mingkun Zhao; Hui Chen; Xing Liu; Jianwei Chen; David M Lonard; Li Qin; Jianming Xu; Xiaosong Wang; Feng Li; Bert W O'Malley; Jin Wang
Journal:  PLoS One       Date:  2015-10-02       Impact factor: 3.240

4.  Low expression of mixed lineage kinase domain-like protein is associated with poor prognosis in ovarian cancer patients.

Authors:  Ling He; Kuan Peng; Yizhi Liu; Jing Xiong; Fu-Fan Zhu
Journal:  Onco Targets Ther       Date:  2013-10-30       Impact factor: 4.147

5.  Constructing an integrated genetic and epigenetic cellular network for whole cellular mechanism using high-throughput next-generation sequencing data.

Authors:  Bor-Sen Chen; Cheng-Wei Li
Journal:  BMC Syst Biol       Date:  2016-02-20

6.  Phosphorylation of steroid receptor coactivator-3 (SRC-3) at serine 857 is regulated by the p38MAPK-MK2 axis and affects NF-κB-mediated transcription.

Authors:  Anup Shrestha; Henrike Bruckmueller; Hanne Kildalsen; Gurjit Kaur; Matthias Gaestel; Hilde Ljones Wetting; Ingvild Mikkola; Ole-Morten Seternes
Journal:  Sci Rep       Date:  2020-07-09       Impact factor: 4.379

Review 7.  Role for Growth Regulation by Estrogen in Breast Cancer 1 (GREB1) in Hormone-Dependent Cancers.

Authors:  Meng Cheng; Stephanie Michalski; Ramakrishna Kommagani
Journal:  Int J Mol Sci       Date:  2018-08-28       Impact factor: 5.923

Review 8.  The Role of Androgen Receptor Signaling in Ovarian Cancer.

Authors:  Taichi Mizushima; Hiroshi Miyamoto
Journal:  Cells       Date:  2019-02-19       Impact factor: 6.600

9.  Src-1 and SP2 promote the proliferation and epithelial-mesenchymal transition of nasopharyngeal carcinoma.

Authors:  Jingjing Zhang; Yuanyuan Yang; Hongyu Liu; Hongyi Hu
Journal:  Open Med (Wars)       Date:  2021-07-15

10.  Risk prediction model for epithelial ovarian cancer using molecular markers and clinical characteristics.

Authors:  Meiying Zhang; Guanglei Zhuang; Xiangjun Sun; Yanying Shen; Aimin Zhao; Wen Di
Journal:  J Ovarian Res       Date:  2015-10-21       Impact factor: 4.234

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.