Expression Profiling in Ovarian Clear Cell Carcinoma
2003; Elsevier BV; Volume: 163; Issue: 6 Linguagem: Inglês
10.1016/s0002-9440(10)63605-x
ISSN1525-2191
AutoresAkira Tsuchiya, Michiie Sakamoto, Jun Yasuda, Makoto Chuma, Tsutomu Ohta, Misao Ohki, Toshiharu Yasugi, Yuji Taketani, Setsuo Hirohashi,
Tópico(s)RNA Research and Splicing
ResumoOf all of the epithelial ovarian cancers, clear cell carcinoma (CCC) of the ovary has the worst prognosis. We applied the oligonucleotide array technique to identify genes generally involved in CCC. Of the ∼12,600 genes that were analyzed, 28 were expressed significantly differently between four CCC and seven non-CCC cell lines. Among 16 up-regulated genes in CCC, we further investigated a transcription factor, hepatocyte nuclear factor-1β (HNF-1β). We validated up-regulation of HNF-1β in CCC in terms of both mRNA and protein level using real-time quantitative reverse transcriptase-polymerase chain reaction and immunoblotting. Immunohistochemical analysis of 83 surgically resected ovarian cancers showed that almost all CCC specimens (21 of 22 cases) had nuclear staining for HNF-1β, whereas most non-CCC specimens (60 of 61 cases) showed no immunostaining or only focal and faint staining in the nucleus. Furthermore, we investigated the significance of HNF-1β expression in CCC using RNA interference. The reduction of HNF-1β expression by RNA interference induced apoptotic cell death in ovarian CCC cells, which was confirmed by terminal dUTP nick-end labeling and fluorescence-activated cell-sorting analyses. Our results suggest that HNF-1β is not only an excellent CCC-specific molecular marker but also a molecular target for therapy of ovarian CCC. Of all of the epithelial ovarian cancers, clear cell carcinoma (CCC) of the ovary has the worst prognosis. We applied the oligonucleotide array technique to identify genes generally involved in CCC. Of the ∼12,600 genes that were analyzed, 28 were expressed significantly differently between four CCC and seven non-CCC cell lines. Among 16 up-regulated genes in CCC, we further investigated a transcription factor, hepatocyte nuclear factor-1β (HNF-1β). We validated up-regulation of HNF-1β in CCC in terms of both mRNA and protein level using real-time quantitative reverse transcriptase-polymerase chain reaction and immunoblotting. Immunohistochemical analysis of 83 surgically resected ovarian cancers showed that almost all CCC specimens (21 of 22 cases) had nuclear staining for HNF-1β, whereas most non-CCC specimens (60 of 61 cases) showed no immunostaining or only focal and faint staining in the nucleus. Furthermore, we investigated the significance of HNF-1β expression in CCC using RNA interference. The reduction of HNF-1β expression by RNA interference induced apoptotic cell death in ovarian CCC cells, which was confirmed by terminal dUTP nick-end labeling and fluorescence-activated cell-sorting analyses. Our results suggest that HNF-1β is not only an excellent CCC-specific molecular marker but also a molecular target for therapy of ovarian CCC. Epithelial ovarian cancer has the worst prognosis of all gynecological malignancies.1Scully RE Young RH Clement PB Rosai J Tumors of the Ovary, Maldeveloped Gonads, Fallopian Tube, and Broad Ligament. Armed Forces Institute of Pathology, Washington DC1999: 27-50Google Scholar Since the emergence of platinum-based chemotherapy, the survival rate of patients with epithelial ovarian cancer has improved dramatically.2Piver MS Ovarian carcinoma. A decade of progress.Cancer. 1984; 54: 2706-2715Crossref PubMed Scopus (90) Google Scholar Debulking surgery and adjuvant chemotherapy (such as a combination of paclitaxel and carboplatin) have now gained a position as the standard therapy for epithelial ovarian cancer.3Parmar MKB Adams M Balestrino M Bertelsen K Bonazzi C Calvert H Colombo N Delaloye JF Durando A Guthrie D Hagen B Harper P Mangioni C Perren T Poole C Qian W Rustin G Sandercock J Tumolo S Torri V Vecchione F Tinazzi A Uscinska B Collins S Flann M Buda A Taylor B Tannock I Souhami R Granzia-Valsecchi M 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.Lancet. 2002; 360: 505-515Abstract Full Text Full Text PDF PubMed Scopus (512) Google Scholar However, we still face many problems in the therapy of epithelial ovarian cancer. One of the most difficult is the treatment of clear cell carcinoma (CCC). The incidence of CCC among epithelial ovarian cancers is not high (∼10%), but patients with CCC have a significantly worse prognosis than patients with serous carcinoma.4Tammela J Geisler JP Eskew Jr, PN Geisler HE Clear cell carcinoma of the ovary: poor prognosis compared to serous carcinoma.Eur J Gynaecol Oncol. 1998; 19: 438-440PubMed Google Scholar, 5O'Brien ME Schofield JB Tan S Fryatt I Fisher C Wiltshaw E Clear cell epithelial ovarian cancer (mesonephroid): bad prognosis only in early stages.Gynecol Oncol. 1993; 49: 250-254Abstract Full Text PDF PubMed Scopus (98) Google Scholar One of the reasons why CCC has such a poor prognosis is its low response to standard platinum-based chemotherapy.6Goff BA Sainz de la Cuesta R Muntz HG Fleischhacker D Ek M Rice LW Nikrui N Tamimi HK Cain JM Greer BE Fuller Jr, AF Clear cell carcinoma of the ovary: a distinct histologic type with poor prognosis and resistance to platinum-based chemotherapy in stage III disease.Gynecol Oncol. 1996; 60: 412-417Abstract Full Text PDF PubMed Scopus (317) Google Scholar From a pathogenetic viewpoint, CCC has a number of features distinguishing it from other epithelial ovarian cancers. The percentage of patients with stage I disease is significantly higher in patients with CCC (48.5%) than in those with serous adenocarcinoma (16.6%),7Sugiyama T Kamura T Kigawa J Terakawa N Kikuchi Y Kita T Suzuki M Sato I Taguchi K Clinical characteristics of clear cell carcinoma of the ovary: a distinct histologic type with poor prognosis and resistance to platinum-based chemotherapy.Cancer. 2000; 88: 2584-2589Crossref PubMed Scopus (698) Google Scholar which means the properties of invasion differ between CCC and non-CCCs. The incidence of p53 mutation differs between CCC (0%) and endometrioid adenocarcinoma (63%).8Okuda T Otsuka J Sekizawa A Saito H Makino R Kushima M Farina A Kuwano Y Okai T p53 mutations and overexpression affect prognosis of ovarian endometrioid cancer but not clear cell cancer.Gynecol Oncol. 2003; 88: 318-325Abstract Full Text Full Text PDF PubMed Scopus (85) Google Scholar The loss of heterozygosity pattern differs between CCC and non-CCCs.9Okada S Tsuda H Takarabe T Yoshikawa H Taketani Y Hirohashi S Allelotype analysis of common epithelial ovarian cancers with special reference to comparison between clear cell adenocarcinoma with other histological types.Jpn J Cancer Res. 2002; 93: 798-806Crossref PubMed Scopus (27) Google Scholar Immunohistochemical analysis has revealed that CCC shows trends such as weak expression of both p53 and cyclin A and markedly increased expression of both p21 and cyclin E compared with the other histological subtypes.10Shimizu M Nikaido T Toki T Shiozawa T Fujii S Clear cell carcinoma has an expression pattern of cell cycle regulatory molecules that is unique among ovarian adenocarcinomas.Cancer. 1999; 85: 669-677Crossref PubMed Scopus (84) Google Scholar Glutathione peroxidase 3 (GPX3) is overexpressed in CCC, which may explain the cancer's chemoresistance.11Hough CD Cho KR Zonderman AB Schwartz DR Morin PJ Coordinately up-regulated genes in ovarian cancer.Cancer Res. 2001; 61: 3869-3876PubMed Google Scholar Considering these facts, it is evident that CCC is not just another type of epithelial ovarian cancer but a distinct entity, and there is a need to determine its molecular pathogenesis if we are to improve its prognosis. Until the establishment of the genome-wide expression-analyzing technique such as serial analysis of gene expression12Velculescu VE Zhang L Vogelstein B Kinzler KW Serial analysis of gene expression.Science. 1995; 270: 484-487Crossref PubMed Scopus (3633) Google Scholar or cDNA microarray13Schena M Shalon D Davis RW Brown PO Quantitative monitoring of gene expression patterns with a complementary DNA microarray.Science. 1995; 270: 467-470Crossref PubMed Scopus (7711) Google Scholar, 14Lockhart DJ Dong H Byrne MC Follettie MT Gallo MV Chee MS Mittmann M Wang C Kobayashi M Horton H Brown EL Expression monitoring by hybridization to high-density oligonucleotide arrays.Nat Biotechnol. 1996; 14: 1675-1680Crossref PubMed Scopus (2831) Google Scholar there was only fragmentary knowledge about the molecular pathogenesis of epithelial ovarian cancer. Since then, there have been extensive studies and rapid progress in our understanding of the molecular pathogenesis of various tumors15Golub TR Slonim DK Tamayo P Huard C Gaasenbeek M Mesirov JP Coller H Loh ML Downing JR Caligiuri MA Bloomfield CD Lander ES Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.Science. 1999; 286: 531-537Crossref PubMed Scopus (9355) Google Scholar, 16Higgins JP Shinghal R Gill H Reese JH Terris M Cohen RJ Fero M Pollack JR van de Rijn M Brooks JD Gene expression patterns in renal cell carcinoma assessed by complementary DNA microarray.Am J Pathol. 2003; 162: 925-932Abstract Full Text Full Text PDF PubMed Scopus (223) Google Scholar, 17Varambally S Dhanasekaran SM Zhou M Barrette TR Kumar-Sinha C Sanda MG Ghosh D Pienta KJ Sewalt RG Otte AP Rubin MA Chinnaiyan AM The polycomb group protein EZH2 is involved in progression of prostate cancer.Nature. 2002; 419: 624-629Crossref PubMed Scopus (2270) Google Scholar including epithelial ovarian cancer.18Wang K Gan L Jeffery E Gayle M Gown AM Skelly M Nelson PS Ng WV Schummer M Hood L Mulligan J Monitoring gene expression profile changes in ovarian carcinomas using cDNA microarray.Gene. 1999; 229: 101-108Crossref PubMed Scopus (286) Google Scholar, 19Hough CD Sherman-Baust CA Pizer ES Montz FJ Im DD Rosenshein NB Cho KR Riggins GJ Morin PJ Large-scale serial analysis of gene expression reveals genes differentially expressed in ovarian cancer.Cancer Res. 2000; 60: 6281-6287PubMed Google Scholar, 20Ono K Tanaka T Tsunoda T Kitahara O Kihara C Okamoto A Ochiai K Takagi T Nakamura Y Identification by cDNA microarray of genes involved in ovarian carcinogenesis.Cancer Res. 2000; 60: 5007-5011PubMed Google Scholar, 21Welsh JB Zarrinkar PP Sapinoso LM Kern SG Behling CA Monk BJ Lockhart DJ Burger RA Hampton GM Analysis of gene expression profiles in normal and neoplastic ovarian tissue samples identifies candidate molecular markers of epithelial ovarian cancer.Proc Natl Acad Sci USA. 2001; 98: 1176-1181Crossref PubMed Scopus (578) Google Scholar, 22Schwartz DR Kardia SL Shedden KA Kuick R Michailidis G Taylor JM Misek DE Wu R Zhai Y Darrah DM Reed H Ellenson LH Giordano TJ Fearon ER Hanash SM Cho KR Gene expression in ovarian cancer reflects both morphology and biological behavior, distinguishing clear cell from other poor-prognosis ovarian carcinomas.Cancer Res. 2002; 62: 4722-4729PubMed Google Scholar Although such studies based on the genome-wide expression analysis have identified many novel genes involved in ovarian cancer, the function and significance of almost all of such genes still remain unknown. Here, we demonstrated that a distinction could be made between four CCC cell lines and seven non-CCC cell lines in terms of their molecular signatures. We found that hepatocyte nuclear factor-1β (HNF-1β), a sequence-specific transcription factor, is up-regulated at both the mRNA and protein level in CCC, unlike other epithelial ovarian cancers, using immunoblotting of 11 ovarian cancer cell lines and immunohistochemistry of 83 surgically resected specimens. As immunohistochemical analysis revealed that HNF-1β expression was tightly linked to CCC, we furthermore investigated the significance of HNF-1β expression in CCC using RNA interference (RNAi), a new gene-silencing technique.23Fire A Xu S Montgomery MK Kostas SA Driver SE Mello CC Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans.Nature. 1998; 391: 806-811Crossref PubMed Scopus (12092) Google Scholar, 24Kennerdell JR Carthew RW Use of dsRNA-mediated genetic interference to demonstrate that frizzled and frizzled 2 act in the wingless pathway.Cell. 1998; 95: 1017-1026Abstract Full Text Full Text PDF PubMed Scopus (956) Google Scholar, 25Elbashir SM Harborth J Lendeckel W Yalcin A Weber K Tuschl T Duplexes of 21-nucleotide RNAs mediate RNA interference in cultured mammalian cells.Nature. 2001; 411: 494-498Crossref PubMed Scopus (8243) Google Scholar Ovarian CCC cells were transfected with short interference RNA (siRNA) targeted against the HNF-1β gene. Terminal dUTP nick-end labeling (TUNEL) and fluorescence-activated cell-sorting (FACS) analyses revealed that the reduction of HNF-1β induced apoptotic cell death in ovarian CCC cells. Our data indicate that HNF-1β would be not only an excellent CCC-specific molecular marker but also a molecular target for the therapy of ovarian CCC. RMG-1, RMG-2, and RMUG-L cell lines were kindly provided by Dr. S. Nozawa (Keio University, Tokyo, Japan). JHOC-5, JHOS-2, and JHOS-3 were generously provided by Dr. H. Ishikawa (Tokyo Jikeikai Medical School, Tokyo, Japan). OMC-3 was kindly provided by Dr. T. Yamada (Osaka Medical College, Osaka, Japan). MCAS was obtained from the Japanese Cancer Research Resources Bank, Tokyo, Japan. OV-90, TOV-21G, TOV-112D, and HeLa cells were obtained from the American Type Culture Collection (Manassas, VA). Abbreviations used for these cell lines and the cell line histologies are shown in Table 1. All cell lines were cultured in RPMI 1640 supplemented with 10% fetal bovine serum, 100 U/ml penicillin, and 100 μg/ml streptomycin in a humidified atmosphere of 5% CO2 and 95% air at 37°C.Table 1Analyzed Ovarian Cancer Cell LinesAbbreviationCell nameHistologyC1RMG-2Clear cellC2RMG-1Clear cellC3JHOC-5Clear cellC4TOV-21GClear cellE1TOV-112DEndometrioidM1RMUG-LMucinousM2MCASMucinousM3OMC-3MucinousS1JHOS-3SerousS2OV-90SerousS3JHOS-2Serous Open table in a new tab Total RNA was extracted from each cell line using Trizol reagent (Invitrogen, Carlsbad, CA) according to the manufacturer's instructions, and then treated with DNase I (Promega, Madison, WI). The cRNA target was synthesized from 5 μg of total RNA derived from each sample using a Super Script Choice System (Invitrogen) and the BioArray High Yield RNA Transcript Labeling kit (Enzo Diagnostics, Farmingdale, NY) according to the manufacturer's instructions. Hybridization of each cRNA target to human U95Av2 oligonucleotide probe arrays (corresponding to 12,686 human genes and expressed sequence tags; Affymetrix, Santa Clara, CA) and detection of the signals were performed as instructed by the manufacturer. Absolute analysis was performed with Affymetrix Microarray Suite 4.0 software. The hybridization intensity data were normalized to 1000 total signal intensities for each array. The data were further filtered and analyzed by GeneSpring Software (version 4.2.1; Silicon Genetics, San Carlos, CA). From total RNA sample, template cDNA was synthesized with an oligo (dT)12–18 primer (Invitrogen) and Omniscript Reverse Transcriptase (Qiagen, Hilden, Germany). Real-time quantitative RT-PCR was performed with a QuantiTect SYBR Green PCR kit (Qiagen) and a GeneAmp 7700 Sequence Detector (Applied Biosystems, Foster City, CA) under the following conditions: one cycle at 95°C for 15 minutes, then 40 cycles at 95°C for 15 seconds, 55°C for 30 seconds, and 72°C for 30 seconds. For standardization of the amount of RNA, expression of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) in each sample was quantified. The primer sets for amplification of HNF-1β, lamin, and GAPDH cDNA were as follows: HNF-1β forward, 5′-GCCCACACACCACTTACTTCG-3′; and reverse, 5′-GTCCGTCAGGTAAGCAGGGAC-3′; lamin forward, 5′-CTGCGCAACAAGTCCAATGAG-3′; and reverse, 5′-CAGGGTGAACTTTGGTGGGAAC-3′; GAPDH forward, 5′-AGGAAGAGAGAGACCCTCACTGC-3′; and reverse, 5′-ATGACAAGGTGCGGCTCC-3′. Quantitative RT-PCR was performed at least three times, including a no-template control as a negative control. Statistical analyses were performed by the Mann-Whitney U-test. For immunoblot analysis, cells were lysed with lysis buffer [50 mmol/L Tris-HCl (pH 7.4), 150 mmol/L NaCl, 1% Triton X-100, 1 mmol/L phenylmethyl sulfonyl fluoride, and complete protease inhibitor cocktail tablet (Roche Diagnostics, Basel, Switzerland)]. The lysate was centrifuged and the supernatant was prepared. Equal amount of proteins were resolved by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (10%) and transferred to polyvinylidene difluoride membrane (Immobilon; Millipore, Billerica, MA). Nonspecific sites on the membrane were blocked by incubation for 90 minutes at ambient temperature with 5% (w/v) nonfat dry milk in phosphate-buffered saline (PBS). All of the membranes were then incubated overnight at 4°C with goat polyclonal antibody for HNF-1β (sc-7411; Santa Cruz Biotechnology, Santa Cruz, CA), mouse monoclonal antibody for lamin A/C (612163; BD Biosciences, San Jose, CA) and mouse monoclonal antibody for α-tubulin (sc-8035; Santa Cruz Biotechnology) as a loading control in the same blocking solution. The membranes were then washed and incubated for 90 minutes at ambient temperature with horseradish peroxidase-conjugated secondary antibodies (Santa Cruz Biotechnology). Immunocomplexes were visualized using an enhanced chemiluminescence detection system (Amersham Pharmacia Biotech, Buckinghamshire, UK). We investigated a total of 83 epithelial ovarian cancers surgically resected at the National Cancer Center Hospital between 1998 and 2001. The patients' ages ranged from 30 to 84 years (mean, 55.6 years), and none of the patients had received chemotherapy or any other treatment preoperatively. Their detailed clinicopathological features are summarized in Table 2. Ten cases of ovarian endometriosis and 10 cases of normal ovarian surface epithelium from patients with other nonneoplastic gynecological diseases were also investigated. The pathological diagnoses were made according to the criteria of the World Health Organization and the International Federation of Gynecology and Obstetrics (FIGO).26Serov SF Scully RE Sobin LH Histologic typing of ovarian tumors.International Histologic Classification of Tumors, no. 9. World Health Organization, Geneva1973Google ScholarTable 2Clinicopathological Features of Surgically Resected SpecimensCharacteristicsClear cell (%)Serous (%)Mucinous (%)Endometrioid (%)Age 75%). The Mann-Whitney U-test and chi-square test were used to analyze the statistical significance of the relationship between HNF-1β expression and the clinicopathological variables. HNF-1β siRNA, which was chemically synthesized 21-nucleotide double-stranded RNA, was obtained from Dharmacon Research Inc. (Lafayette, CO). The HNF-1β siRNA was targeted to the coding regions 1276 to 1296 (AAUCCCCAGCAAUCUCAAAAC) to the first nucleotide of the start codon (GenBank accession no. X58840). Control siRNAs targeted to luciferase GL2 and lamin A/C25Elbashir SM Harborth J Lendeckel W Yalcin A Weber K Tuschl T Duplexes of 21-nucleotide RNAs mediate RNA interference in cultured mammalian cells.Nature. 2001; 411: 494-498Crossref PubMed Scopus (8243) Google Scholar were obtained from Dharmacon Research Inc. Cells were plated at 2 × 105 cells per well in a six-well plate for real-time quantitative RT-PCR, immunoblot, TUNEL, and FACS analysis. Twenty-four hours after plating, the cells were transfected with a final concentration of 100 nmol/L of siRNA using siPORT Lipid (Ambion, Austin, TX) according to the manufacturer's instructions. Apoptosis was detected by TUNEL assay and FACS analysis. The TUNEL assay was performed using an In Situ Cell Death Detection kit (Roche Diagnostics) according to the manufacturer's instructions. Then the nuclei were counterstained with VectaShield DAPI (4,6-diamidino-2-phenylindole; Vector Laboratories), and viewed with a Zeiss LSM410 microscope (Zeiss, Thornwood, NY). The number of TUNEL-positive nuclei was counted and divided by the number of DAPI-stained nuclei to calculate the percentage of TUNEL-positive cells. For FACS analysis, 6, 12, 18, or 24 hours after transfection with siRNA, adherent and detached cells were combined and fixed overnight with 70% ethanol at 4°C overnight. After two rinses with PBS, the cells were incubated for 20 minutes with 1 ml of PBS containing 1 mg of ribonuclease A at 37°C, and then stained in 1 ml of PBS containing 50 μg of propidium iodide. A total of 2 × 104 cells were then analyzed in a flow cytometer (FACScalibur; Becton Dickinson, Franklin Lakes, NJ), and the sub-G1 peak was quantified using CELLQuest software. To identify genes expressed differently between CCC and non-CCCs, we compared the gene expressions of four ovarian CCC cell lines with those of seven cell lines of other histologies using oligonucleotide array. We filtered all genes, with the following limits: 1) present (ie, unambiguously expressed in the sample) in at least 5 of 11 samples; 2) average difference of more than 1000 in at least 5 of 11 samples (mean difference in signal intensity between perfect match and mismatch probe pairs); 3) Mann-Whitney U-test with significance set at P < 0.05 to identify genes expressed differently between CCCs and non-CCCs. Using the above criteria, we selected 207 differently expressed genes from 12,686 probe sets. Furthermore, we listed genes that met an additional limit: 4) more than a threefold increase in the average difference between two groups, to identify genes with more significant difference of expression in CCC or non-CCC cells (Figure 1). Sixteen genes were up-regulated and 12 were down-regulated in CCC compared with non-CCCs. Of the genes listed in Figure 1, we focused on a transcription factor HNF-1β because it is a well-characterized transcription factor playing an important role in the embryonal development,27Lazzaro D De Simone V De Magistris L Lehtonen E Cortese R LFB1 and LFB3 homeoproteins are sequentially expressed during kidney development.Development. 1992; 114: 469-479Crossref PubMed Google Scholar but its up-regulation is rare among the cancerous tissue other than hepatocellular carcinoma28Wang W Hayashi Y Ninomiya T Ohta K Nakabayashi H Tamaoki T Itoh H Expression of HNF-1 alpha and HNF-1 beta in various histological differentiations of hepatocellular carcinoma.J Pathol. 1998; 184: 272-278Crossref PubMed Scopus (35) Google Scholar and the significance of its expression in cancerous tissue is still unknown. As HNF-1β was the most abundantly up-regulated transcription factor, we speculated that it contributes to the characteristic biological behavior of CCC by regulating its downstream target genes. First, we analyzed the expression level of HNF-1β mRNA by real-time quantitative RT-PCR (Figure 2A). The relative expression levels of HNF-1β mRNA normalized with GAPDH mRNA, as measured by real-time quantitative RT-PCR, were closely correlated with those obtained by microarray analysis. The relative expression levels of HNF-1β mRNA in CCCs (8.75 ± 3.89) were on average 11.6-fold higher than those in non-CCCs (0.75 ± 1.09) (P = 0.008 by U-test). We next examined the expression of HNF-1β protein using anti-HNF-1β antibody. Immunoblot detection of HNF-1β in a series of ovarian cancer cell lines is shown in Figure 2B. The Mr 70,000 band corresponding to HNF-1β protein was detected in all CCC cell lines. The Mr 55,000 band detected in C1 and C2 was considered to be corresponding to a splice variant protein of HNF-1β because there are three HNF-1β isoforms.29Bach I Yaniv M More potent transcriptional activators or a transdominant inhibitor of the HNF1 homeoprotein family are generated by alternative RNA processing.EMBO J. 1993; 12: 4229-4242Crossref PubMed Scopus (112) Google Scholar No specific band was detected other than these two HNF-1β-specific bands. The intensity of the Mr 70,000 band in each cell line was correlated with the mRNA expression level obtained from quantitative RT-PCR analysis. Little or no reactivity for HNF-1β was observed in any of the non-CCC cell lines except for M1. To determine whether HNF-1β is also up-regulated in surgically resected specimens of CCC at the protein level, for immunohistochemical analysis we used the same anti-HNF-1β antibody that we had used for immunoblot analysis (Figure 3). Almost all of the CCCs showed nuclear staining (Figure 3; A to C), but most non-CCCs showed no immunostaining or only focal and faint staining in the nucleus (Figure 3; D to G). No cases of benign endometriosis showed nuclear staining for HNF-1β (Figure 3H). Also, no cases of normal ovarian surface epithelium, which is considered to be the origin of epithelial ovarian cancer, showed nuclear staining for HNF-1β (Figure 3I). The HNF-1β immunostaining score for CCCs (4.22 ± 0.85) was significantly higher than that for non-CCCs (0.31 ± 0.62) (P < 0.0001 by U-test) (Figure 4). The different HNF-1β expression patterns (high or low HNF-1β expression) did not correlate with patient age or histological differentiation (Table 3). The P value for the difference in expression pattern of HNF-1β between the early FIGO stage (stage I, II) and the advanced stage (stage III, IV) was significant (P = 0.041 by chi-square test) (Table 3), but we considered that this significance was related to the earlier FIGO stage distribution of CCCs and the higher HNF-1β immunostaining score for CCCs. Indeed, there was no significant difference between the HNF-1β score for earlier-stage CCCs (4.16 ± 0.57, 18 cases) and that for advanced-stage CCCs (4.50 ± 0.99, four cases) (P = 0.670 by U-test). Therefore, essentially, no specific correlation was found between these immunostaining scores and FIGO stage.Table 3Relationships Between HNF-1β Expression and Clinicopathological Features in Epithelial Ovarian Cancers*Chi-square test.nHNF-1β expression high group (score 3 to 5)HNF-1β expression low group (score 0 to 2)P valueAll patients8322 (27%)61 (73%)Age <605715 (26%)42 (74%) ≥60267 (27%)19 (73%)0.953Histology Clear cell2221 (95%)1 (5%) Serous390 (0%)39 (100%) Mucinous110 (0%)11 (100%) Endometrioid111 (9%)10 (91%)<0.0001Histologic differentiation Well4111 (27%)30 (73%) Moderate278 (30%)19 (70%) Poor153 (20%)12 (80%)0.793FIGO stage I/II5318 (34%)35 (66%) III/IV304 (13%)26 (87%)0.041* Chi-square test. Open table in a new tab To investigate whether the up-regulated expression of HNF-1β in CCC has biological significance, we conducted functional analysis by reduction of HNF-1β expression with RNAi. Using real-time quantitative RT-PCR, we first tested the ability of siRNAs to reduce the endogenous level of lamin and HNF-1β mRNA in the TOV-21G, JHOC-5, RMG-1, and RMG-2 ovarian CCC cell lines (Figure 5A). Lamin siRNA significantly reduced the expression of lamin mRNA to 44 ± 6% (TOV-21G) or to 42 ± 7% (JHOC-5) of the level in cells treated with the transfection reagent only, but it did not reduce the expression of HNF-1β mRNA. HNF-1β siRNA significantly reduced the expression of HNF-1β mRNA to 27 to 45% (TOV-21G) or to 50 ± 12% (JHOC-5) of the level in cells treated with the transfection reagent only, but it did not reduce the expression of lamin mRNA. Lamin or HNF-1β siRNA did not reduce lamin or HNF-1β mRNA in RMG-1 or RMG-2 cell lines (data not shown). Therefore, by using siRNA we successfully induced gene-specific silencing in the TOV-21G and JHOC-5 cell lines. Next, using immunoblot analysis, we examined whether these siRNAs also reduce the expression of lamin or HNF-1β protein in the TOV-21G and JHOC-5 cell lines (Figure 5B). Lamin siRNA reduced the expression of lamin protein. HNF-1β siRNA reduced the expression of HNF-1β protein time dependently, and the intensity of the HNF-1β protein band almost reached the background level 24 hours after transfection in TOV-21G and JHOC-5 cells. The effect was specific because lamin or HNF-1β siRNA reduced only the lamin or HNF-1β protein, respectively, and siRNA targeted to luciferase, for which TOV-21G or JHOC-5 has no endogenous expression, did not change the expression of any protein. It was observed that TOV-21G and JHOC-5 cells transfected with HNF-1β siRNA
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