Obstetrics & Gynecology:
Overexpression of Karyopherin-2 in Epithelial Ovarian Cancer and Correlation With Poor Prognosis
Zheng, Min MD; Tang, Li MD; Huang, Long MD; Ding, Hui MD; Liao, Wen-Ting PhD; Zeng, Mu-Sheng PhD; Wang, Hui-Yun PhD
From the State Key Laboratory of Oncology in Southern China and the Department of Gynecology, Cancer Center, Sun Yat-sen University, Guangzhou, Guangdong, China.
Supported by the Guangdong natural science fund (grant number 2007B031513006) and State Key Laboratory of Oncology in Southern China Science Fund (grant number 030041060004).
The authors thank Prof Weng-Lin Huang for providing EOC cell lines.
Corresponding author: Min Zheng, MD, State Key Laboratory of Oncology in Southern China and Department of Gynecology, Cancer Center, Sun Yat-sen University, 651 Dongfeng Road East, Guangzhou, Guangdong 510060, PR China; e-mail: email@example.com.
Financial Disclosure The authors did not report any potential conflicts of interest.
OBJECTIVES: To evaluate karyopherin 2 (KPNA2) as a biomarker for epithelial ovarian cancer.
METHODS: A candidate oncogene, KPNA2, was identified in gene microarray assays of epithelial ovarian cancer tissues compared with normal human ovarian surface epithelial tissues. Differences in expression were further validated by real-time polymerase chain reaction and Western blotting. KPNA2 expression patterns in epithelial ovarian cancer tissues were determined using immunohistochemistry and were compared with specific clinicopathologic features of the patient specimens analyzed. Factors associated with patient survival were also statistically analyzed.
RESULTS: KPNA2 was found to be upregulated approximately eightfold in epithelial ovarian cancer tissues compared with human ovarian surface epithelial tissues, and overexpression was detected at the level of both transcription and translation. Immunohistochemical assays detected positive KPNA2 expression (++ or +++) in 50 of 102 (49.0%) epithelial ovarian cancer specimens, whereas negative KPNA2 expression (− or +) was observed in all of the human ovarian surface epithelial tissues analyzed. KPNA2 overexpression was also found to be significantly associated with specific histologic type, an advanced stage, a high histologic grade, and tumor recurrence (P<.05). The 5-year overall survival rate for KPNA2-negative compared with KPNA2-positive patients was 73.1% and 60.5%, respectively (P<.05).
CONCLUSION: KPNA2 may play an important role in the development, differentiation, and carcinogenesis of epithelial ovarian cancer and therefore could be an indicator of poor prognosis for patients with epithelial ovarian cancer.
LEVEL OF EVIDENCE: II
Ovarian cancer is the leading cause of death among gynecologic malignancies in women, with a 5-year survival rate of 35-40% for patients who receive optimal treatment.1 To improve this survival rate, the etiology and development of ovarian cancer needs to be better understood. Epithelial ovarian cancer is the most common pathologic type of ovarian cancer with an occurrence rate of 80% among diagnosed ovarian cancers. Currently, the only validated marker for epithelial ovarian cancer is CA 125. However, CA 125 is only a robust marker for treatment response or disease progression and is not a diagnostic or prognostic marker.2 Thus, the identification of novel, specific genes and their corresponding protein products that can be effectively used as diagnostic reagents, therapeutic targets, prognostic markers, or all of these for ovarian cancer is of critical importance.
Several oncogenes have been reported to be associated with ovarian cancer, including c-erbB2,3 inhibin, and prostasin4 as well as the suppressor genes p53, BRCA1, and IGFBP-3.5 However, direct evidence is needed to confirm the clinical use of these oncogenes. A useful approach for discovering tumor-specific markers has been to compare gene expression profiles of neoplastic tissues and analogous untransformed tissues. However, although this approach has identified candidate molecular markers of epithelial ovarian cancer,6–9 the clinical value of these markers has not been unequivocally validated.
The objective of this study was to identify a useful biomarker for epithelial ovarian cancer. In this study, gene microarrays were used to screen for tumor-specific genes that may represent diagnostic markers, poor prognosis indicators, or both for epithelial ovarian cancer. In these experiments, karyopherin 2 (KPNA2) was found to be upregulated in epithelial ovarian cancer tissues compared with normal human ovarian surface epithelial tissues and therefore was selected for further study. Changes in mRNA and protein levels of KPNA2 were detected using real-time polymerase chain reaction reverse transcription-polymerase chain reaction (PCR), real-time PCR, Western blotting, and immunohistochemistry methods. Correlation of KPNA2 expression with specific clinicopathologic features of patients with epithelial ovarian cancer was also evaluated.
MATERIALS AND METHODS
Patients diagnosed with epithelial ovarian cancer between 1998 and 2003 at the Cancer Center, Sun Yat-Sen University, Guangzhou, China, underwent oophorosalpingectomy or surgical debulking before administration of chemotherapy. Epithelial ovarian cancer tissues were dissected from the resected tumors, and human ovarian surface epithelial specimens were obtained from ovarian surface epithelium of normal-appearing ovary removed from epithelial ovarian cancer patients (stage IA) with only one ovary involved (based on the principles of surgical management of ovarian cancer, both the normal and disease ovaries should be resected for stage IA patients), which was confirmed by pathologic review. All samples were obtained from the Tissue Bank of Cancer Center, Sun Yat-Sen University. Epithelial ovarian cancer specimens were evaluated by an experienced pathologist and were staged according to the Federation of Gynecology and Obstetrics classification guidelines. Grading and histopathology subtyping of epithelial ovarian cancer specimens was assigned based on criteria of the World Health Organization. Epithelial ovarian cancer cell lines were also established as explants from solid tumors, and the OVCAR-3 and PA-1 cell lines were maintained as well.
There were 102 patients with epithelial ovarian cancer included in this study and the follow-up data were available for all patients. The duration of follow-up ranged from 5 to 128 months and the median follow-up period was 63.53 months. At last contact, 38 of the patients had died (Table 1). This study was approved by the Ethical Committee of the Cancer Center, Sun Yat-Sen University (Guangzhou, China).
For microarray experiments, three human ovarian surface epithelials, one borderline ovarian tumor, and nine epithelial ovarian cancer specimens (including three stage I or II and six stage III or IV specimens) were snap-frozen and stored at −20°C. Total RNA was extracted from 0.1 g of each tissue using Trizol reagent (Invitrogen Life Technologies, Ontario, Canada), and these samples were assessed using ethidium bromide staining before being used to reverse-transcribe cDNA. cRNA probes were generated using the TrueLabeling-AMP Linear RNA Amplification Kit and were hybridized with purified biotin-labeled cRNA and the OHS-802 Oligo GE Array(R) Human Cancer Microarray containing 440 human oncogenes according to the manufacturer's instructions. For data analysis, the Web-based GEArray Expression Analysis Suite program was used.
Total RNA from epithelial ovarian cancer cell lines, nine human ovarian surface epithelials, 11 epithelial ovarian cancers, and six paired samples of human ovarian surface epithelial and epithelial ovarian cancer specimens from six patients were extracted as described previously. Reverse transcription-PCR was performed using the PrimeScriptRT-PCR Kit (TaKaRa Bio, Shiga, Japan) according to the manufacturer's instruction in a T-gradient Biometra PCR thermal cycler (PCR-200). KPNA2 primer pairs included: 5′-CAAGGCTGTGGTAGATGG-3′ (forward) and 5′-GCGGCAAAGATTAGAAAG-3′ (reverse); and glyceraldehyde-3-phosphate dehydrogenase (control) primers included: 5′-AATCCCATCACCATCTTCCA-3′ (forward) and 5′-CCTGCTTCACCACCTTCTTG-3′ (reverse). PCR products were detected with ethidium bromide staining and were semiquantified using Quantity One 1-D Analysis Software.
TaqMan PCR primers and probes for KPNA2 were obtained (Applied Biosystems, Inc.). KPNA2 primers included: 5′-CTGGGACATCAGAACAAACCAAG-3′ (forward) and 5′-ACACTGAGCCATCACCTGCAAT-3′ (reverse), and glyceraldehyde-3-phosphate dehydrogenase (positive control) primers included: 5′-CTCCTCCTGTTCGACAGTCAGC-3′ (forward) and 5′-CCCAATACGACCAAATCCGTT-3′ (reverse). Real-time PCR was carried out according to the TaqMan Universal PCR Master Mix Protocol in an ABI PRISM7700 sequence detection system (Applied Biosystems Inc). The ABI PRISM 7700 Cycler software was used to calculate a threshold cycle number (Ct) value for glyceraldehyde-3-phosphate dehydrogenase and KPNA2 during the log phase of each cycle. KPNA2 levels were normalized to glyceraldehyde-3-phosphate dehydrogenase (GAPDH) (ΔCt=CtKPNA2−CtGAPDH) and were compared with the values obtained from a test sample used as a positive control according to the following formula: 2−ΔΔCt, where ΔΔCt=ΔCtunknown−ΔCtpositive control. To minimize experimental variability, each sample was tested in triplicate and the mean femtogram expression level was calculated.
Ten human ovarian surface epithelials and 15 epithelial ovarian cancer specimens were analyzed. For each specimen, 40 μg of total protein was used for immunoblot analysis as described in Planchamp et al.10 The rabbit polyclonal antibody to KPNA2 (1:500) (ab54489) and goat antirabbit secondary antibody (1:3000; SC2004) were used in the assay. Bound antibody was visualized using the electrochemiluminescence system.
Paraffin-embedded tissues of 15 human ovarian surface epithelial specimens and 102 epithelial ovarian cancer specimens from patients with a median age of 47.2 years (range 19-65 years) were analyzed using immunohistochemical staining described by Song et al.11 Anti-KPNA2 antibody was a rabbit polyclonal antibody (1:500) (ab54489; Abcam plc). Control samples were stained in parallel yet were not incubated with either primary or secondary antibodies. Immunoreactivity was described by the percentage of positive tumor cells (percent positivity) and by the staining intensity (weak, moderate, strong). Slides given scores of (−) or (+) were recorded as negative, and slides given scores of (++) and (+++) were recorded as positive. All results were confirmed by more than two pathologists in a double-blind analysis.
Fisher's exact test was used to compare the differences of KPNA2 expression between epithelial ovarian cancers and human ovarian surface epithelials at the levels of transcription and translation. Pearson's χ2 tests were also applied to study the relationship between KPNA2 expression and histologic type, histologic grade, clinical stage, recurrence, patient age, and optimal cytoreduction of epithelial ovarian cancer performed. Survival curves for both KPNA2-positive and KPNA2-negative patients were plotted using the Kaplan-Meier method12 and were analyzed for statistical differences using log-rank tests.13 Multivariable survival analysis using Cox's regression model was performed. P<.05 was considered statistically significant. All statistical analyses were performed using SPSS 17.0.
For microarray experiments, three human ovarian surface epithelials, one borderline ovarian tumor, three stage I or II epithelial ovarian cancers, and six stage III or IV. Epithelial ovarian cancer specimens were analyzed using the Oligonucleotide Cancer Microarray containing 440 human oncogenes. Comparison of the gene expression profiles for the human ovarian surface epithelial and epithelial ovarian cancer specimens identified 59 genes that were overexpressed in more than 60% of the epithelial ovarian cancer specimens analyzed (Fig. 1). In particular, more than an eightfold (average) increase in KPNA2 expression was detected in epithelial ovarian cancer specimens compared with human ovarian surface epithelial specimens (Fig. 1). Moreover, the lowest levels of KPNA2 expression were detected in the human ovarian surface epithelial specimens and the borderline ovarian tumor specimen, whereas KPNA2 was moderately upregulated in the three stage I or II epithelial ovarian cancer specimens and extensively upregulated in the six stage III or IV epithelial ovarian cancer specimens.
Reverse transcription-PCR assays of KPNA2 expression in 17 epithelial ovarian cancer and human ovarian surface epithelial specimens (Fig. 2A) were consistent with the gene expression patterns detected for KPNA2 in the microarray experiments described previously. Extensive KPNA2 expression was observed in both epithelial ovarian cancer tissues as well as the OVCAR-3 and PA-1 cell lines (Fig. 2B) compared with the human ovarian surface epithelial specimens. These differences were statistically significant (P<.001). Western blotting experiments detected increased expression of KPNA2 in 15 epithelial ovarian cancer specimens compared with 10 human ovarian surface epithelial specimens (Fig. 2D). These differences were also statistically significant (P<.001). Furthermore, real-time PCR assays detected higher levels of KPNA2 mRNA in epithelial ovarian cancer cell lines than in human ovarian surface epithelial specimens (Fig. 2C).
Negative KPNA2 expression (KPNA2−/+) was observed in all human ovarian surface epithelial specimens with 13 of 15 (86.7%) labeled as (−) and two of 15 (13.3%) labeled as (+). In contrast, 50 of 102 (49.0%) epithelial ovarian cancer specimens were labeled with KPNA2 expression levels of (++) or (+++), and 44 of 102 (43.1%) epithelial ovarian cancer specimens were labeled as (+) (Fig. 3A).
Of the 102 patients with epithelial ovarian cancer included in this study, patient follow-up data were available for all patients. The duration of follow-up ranged from 5 to 128 months, the median follow-up period was 63.53 months, and at last contact 38 patients had died. The 5-year overall survival rate for the 102 patients with epithelial ovarian cancer patients was 68%, and univariable analysis showed that age, clinical stage, histologic grade, tumor recurrence, cytoreductive surgery, and KPNA2 expression were factors significantly associated with this survival rate (P<.05) (Table 1). Analysis using Cox multivariable regression also found that clinical stage and histologic grade were significantly associated with the 5-year overall survival rate (P<.05) (Table 2), whereas KPNA2 expression, age, tumor recurrence, and cytoreductive surgery were not identified to be an independent prognostic factors for epithelial ovarian cancers.
Table 3 lists the clinicopathologic features of epithelial ovarian cancer patients whose sepcimens were analyzed for KPNA2 expression in this study. Positive expression of KPNA2 was significantly associated with histologic type, an advanced clinical stage, high histologic grade, and tumor recurrence (each P<.05). Specifically, positive expression of KPNA2 was detected in 60.9% (39 of 64) of serous epithelial ovarian cancer specimens, 30.0% (nine of 30) of mucinous epithelial ovarian cancer specimens, and 25.0% (two of eight) of endometrioid or undifferentiated epithelial ovarian cancer specimens with these differences being statistically significant (P=.007). Based on tumor stage, the frequency of KPNA2 expression in epithelial ovarian cancer specimens was 23.5% (eight of 34) for stage I, 55.6% (10 of 18) for stage II, 65.1% (28 of 43) for stage III, and 57.1% (four of seven) for stage IV. These differences were also statistically significant (P=.003). Moreover, Pearson's χ2 test showed that KPNA2 expression, as a function of clinical stage, was significant (r=0.341, P=.001). The frequency of KPNA2 expression in epithelial ovarian cancers was 25.0% (nine of 36) for grade I specimens, 46.2% (12 of 26) for grade II specimens, and 72.5% (29 of 40) for grade III specimens. The difference in the frequency of KPNA2 expression for these three groups was statistically significant (P<.001). Using a χ2 test, KPNA2 expression was also found to positively correlate with histological grade (r=0.282, P=.041). For patients with tumor recurrence, the frequency of epithelial ovarian cancers with KPNA2 expression was 61.2% (30 of 49) compared with a frequency of 37.7% (20 of 53) for patients without tumor recurrence, and this difference was statistically significant (P=.018). It was found, however, that positive expression of KPNA2 did not correlate with patient age or optimal cytoreduction treatments (Table 3).
Kaplan-Meier survival curves show that patients with epithelial ovarian cancer associated with positive KPNA2 expression had substantially lower survival rates than patients with epithelial ovarian cancer who were KPNA2-negative (P=.046) (Fig. 3B). Using the log-rank test, the 5-year overall survival rate for KPNA2-negative patients (73.1%) was found to be higher than the overall survival rate for KPNA2-positive patients (60.5%) (Table 1).
KPNA2 expression has been detected at the mRNA and protein level in ovarian carcinomas, and a correlation between KPNA2 expression and the specific histologic type, clinical stage, histologic grade, and tumor recurrence was determined. For patients with epithelial ovarian cancer, expression of KPNA2 was found to be an unfavorable prognostic indicator for overall survival.
To identify specific tumor markers that correlate with epithelial ovarian cancer tumorigenesis, gene microarray experiments were performed. Although 59 genes were found to differ in expression between epithelial ovarian cancer and human ovarian surface epithelial specimens, the identities of these genes were not provided because KPNA2 was selected for further study. KPNA2 was found to be expressed at low levels in most of the human ovarian surface epithelial specimens assayed and also in the borderline ovarian tumor specimen and three of the early stage (I or II) epithelial ovarian cancer specimens assayed. In contrast, extensive upregulation of KPNA2 was detected in all of the advanced stage (III or IV) epithelial ovarian cancer specimens. These results suggest that expression of KPNA2 may play an important role in the development and progression of epithelial ovarian cancer tumorigenesis.
KPNA2 (also known as RAG cohort 1 and importin α 1) is a human gene located in 17q24.2. As an adaptor protein associated with the classic nuclear protein import machinery, KPNA2 would be predicted to have a role in the import of signaling factors into the nucleus and the export of response molecules to the cytoplasm.14,15 KPNA2 has also been reported to have an important role in regulating epidermal proliferation and differentiation as well as in activating cellular signaling in blood lymphocytes.16,17 In Russell-Silver syndrome,18 KPNA2 has been shown to possess tumorigenic activity.19,20 There have also been reports implicating KPNA2 expression with human breast carcinogenesis21–23 based on the lack of KPNA2 expression in normal human breast tissue and the overexpression of KPNA2 detected in a majority of human breast cancers.22,24,25 Accordingly, KPNA2 has been hypothesized to be a diagnostic marker of breast cancer, yet it remains unknown whether KPNA2 expression correlates with other types of carcinomas.
Univariable analysis identified patient age, clinical stage, histologic grade, tumor recurrence, cytoreductive surgery, and KPNA2 expression to be significant predictors of epithelial ovarian cancer patient prognosis, whereas multivariable analysis further indicated that both clinical stage and histologic grade were significant independent prognostic factors. Immunohistochemistry studies showed that extensive expression of KPNA2 is associated with specific histologic type, advanced stage, histologic grade, and recurrence of epithelial ovarian cancer. Therefore, although KPNA2 has been found to be a significant predictor of prognosis, it is not an independent prognostic factor. It is possible that KPNA2 may indirectly contribute to the poor prognosis of patients with epithelial ovarian cancer based on its correlation with advanced stage and high histologic grades of epithelial ovarian cancer, and additional studies would be needed to determine whether KPNA2 affects the development, differentiation, carcinogenesis, or all of these for epithelial ovarian cancer and, as such, could represent a diagnostic marker for epithelial ovarian cancer.
Several studies have demonstrated that extensive expression of KPNA2 in patients with breast cancer is associated with a shorter overall survival and recurrence-free survival time.18,22 Furthermore, KPNA2 has been identified as a possible marker for chemoresistance in advanced breast cancers.26 Consistent with these studies, extensive expression of KPNA2 in the epithelial ovarian cancer specimens analyzed was found to strongly correlate with poor prognosis and tumor recurrence in patients with epithelial ovarian cancer. Extensive expression of KPNA2 was also associated with serous-type epithelial ovarian cancer with higher expression levels of KPNA2 detected in serous epithelial ovarian cancer specimens than in mucinous, endometrioid, or undifferentiated epithelial ovarian cancer specimens assayed. Based on these results, we hypothesize that KPNA2 is a specific marker for serous epithelial ovarian cancer.
In conclusion, gene microarray data identified genes with differences in expression between epithelial ovarian cancer and human ovarian surface epithelial specimens, and we report, for the first time, that overexpression of KPNA2 in patients with epithelial ovarian cancer is positively associated with an epithelial ovarian cancer-specific histologic type, advanced tumor stages, high histologic grade, and an increased frequency of tumor recurrence. Patients with epithelial ovarian cancer expressing high levels of KPNA2 also exhibited a substantially lower overall survival rate than KPNA2-negative patients. Thus, our study provides evidence that KPNA2 may play an important role in the development, differentiation, and carcinogenesis of epithelial ovarian cancer and therefore, could be a valuable indicator of poor prognosis for patients with epithelial ovarian cancer.
1.Pisano C, Bruni GS, Facchini G, Marchetti C, Pignata S. Treatment of recurrent epithelial ovarian cancer. Ther Clin Risk Manag 2009;5:421–6.
2.Niloff JM, Klug TL, Schaetzl E, Zurawski VR, Knapp RC, Bast RC. Elevation of serum CA125 in carcinomas of the fallopian tube, endometrium, and endocervix. Am J Obstet Gynecol 1984;148:1057–8.
3.Meyer T, Rustin GJ. Role of tumour markers in monitoring epithelial ovarian cancer. Br J Cancer 2000;82:1535–8.
4.Mok SC, Chao J, Skates S, Wong K, Yiu GK, Muto MG, et al. Prostasin, a potential serum marker for ovarian cancer: identification through microarray technology. J Natl Cancer Inst 2001;93:1458–64.
5.Torng PL, Lee YC, Huang CY, Ye JH, Lin YS, Chu YW, et al. Insulin-like growth factor binding protein-3 (IGFBP-3) acts as an invasion-metastasis suppressor in ovarian endometrioid carcinoma. Oncogene 2008;27:2137–47.
6.Welsh JB, Zarrinkar PP, Sapinoso LM, Kern SG, Behling CA, Monk BJ, et al. Analysis of gene expression profiles in normal and neoplastic ovarian tissue samples identifies candidate molecular markers of epithelial ovarian cancer. Proc Natl Acad Sci U S A 2001;98:1176–81.
7.Tothill RW, Tinker AV, George J, Brown R, Fox SB, Lade S, et al. Novel molecular subtypes of serous and endometrioid ovarian cancer linked to clinical outcome. Clin Cancer Res 2008;14:5198–208.
8.Sunde JS, Donninger H, Wu K, Johnson ME, Pestell RG, Rose GS, et al. Expression profiling identifies altered expression of genes that contribute to the inhibition of transforming growth factor-beta signaling in ovarian cancer. Cancer Res 2006;66:8404–12.
9.Yang N, Kaur S, Volinia S, Greshock J, Lassus H, Hasegawa K, et al. MicroRNA microarray identifies Let-7i as a novel biomarker and therapeutic target in human epithelial ovarian cancer. Cancer Res 2008;68:10307–14.
10.Planchamp C, Hadengue A, Stieger B, Bourquin J, Vonlaufen A, Frossard JL, et al. Function of both sinusoidal and canalicular transporters controls the concentration of organic anions within hepatocytes. Mol Pharmacol 2007;71:1089–97.
11.Song LB, Zeng MS, Liao WT, Zhang L, Mo HY, Liu WL, et al. Bmi-1 is a novel molecular marker of nasopharyngeal carcinoma progression and immortalizes primary human nasopharyngeal epithelial cells. Cancer Res 2006;66:6225–32.
12.Kaplan EL, Meier P. Nonparametric estimation from incomplete observations. J Am Stat Assoc 1958;53:457–81.
13.Mantel N. Evaluation of survival data and two new rank order statistics arising in its consideration. Cancer Chemother Rep 1966;50:163–70.
14.Chook YM, Blobel G. Karyopherins and nuclear import. Curr Opin Struc Biol 2001;11:703–15.
15.Leung SW, Harreman MT, Hodel MR, Hodel AE, Corbett AH. Dissection of the karyopherin alpha nuclear localization signal (NLS)-binding groove: functional requirements for NLS binding. J Biol Chem 2003;278:41947–53.
16.Andrade R, Alonso R, Pena R, Arlucea J, Arechaga J. Localization of importin alpha (Rch1) at the plasma membrane and subcellular redistribution during lymphocyte activation. Chromosoma 2003;112:87–95.
17.Umegaki N, Tamai K, Nakano H, Moritsugu R, Yamazaki T, Hanada K, et al. Differential regulation of karyopherin alpha 2 expression by TGF-beta1 and IFN-gamma in normal human epidermal keratinocytes: evident contribution of KPNA2 for nuclear translocation of IRF-1. J Invest Dermatol 2007;127:1456–64.
18.Dörr SN, Schlicker MN, Hansmann IN. Genomic structure of karyopherin alpha2 (KPNA2) within a low-copy repeat on chromosome 17q23-q24 and mutation analysis in patients with Russell-Silver syndrome. Hum Genet 2001;109:479–86.
19.Fischer N, Kremmer E, Lautscham G, Mueller-Lantzsch N, Grässer FA. Epstein-Barr virus nuclear antigen 1 forms a complex with the nuclear transporter karyopherin alpha2. J Biol Chem 1997;272:3999–4005.
20.Teng SC, Wu KJ, Tseng SF, Wong CW, Kao L. Importin KPNA2, NBS1, DNA repair and tumorigenesis. J Mol Histol 2006;37:293–9.
21.Thakur S, Zhang HB, Peng Y, Le H, Carroll B, Ward T, et al. Localization of BRCA1 and a splice variant identifies the nuclear localization signal. Mol Cell Biol 1997;17:444–52.
22.Dahl E, Kristiansen G, Gottlob K, Klaman I, Ebner E, Hinzmann B, et al. Molecular profiling of laser-microdissected matched tumor and normal breast tissue identifies karyopherin alpha2 as a potential novel prognostic marker in breast cancer. Clin Cancer Res 2006;12:3950–60.
23.Sørlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A 2001;98:10869–74.
24.Sotiriou C, Wirapati P, Loi S, Harris A, Fox S, Smeds J, et al. Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst 2006;98:262–72.
25.Dankof A, Fritzsche FR, Dahl E, Pahl S, Wild P, Dietel M, et al. KPNA2 protein expression in invasive breast carcinoma and matched peritumoral ductal carcinoma in situ. Virchows Arch 2007;451:877–81.
26.Gluz O, Wild P, Meiler R, Diallo-Danebrock R, Ting E, Mohrmann S, et al. Nuclear karyopherin alpha2 expression predicts poor survival in patients with advanced breast cancer irrespective of treatment intensity. Int J Cancer 2008;123:1433–8.
© 2010 by The American College of Obstetricians and Gynecologists.
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