Profiling of actionable gene alterations in ovarian cancer by targeted deep sequencing

  • Authors:
    • Masataka Takenaka
    • Motonobu Saito
    • Reika Iwakawa
    • Nozomu Yanaihara
    • Misato Saito
    • Mamoru Kato
    • Hitoshi Ichikawa
    • Tatsuhiro Shibata
    • Jun Yokota
    • Aikou Okamoto
    • Takashi Kohno
  • View Affiliations

  • Published online on: April 3, 2015
  • Pages: 2389-2398
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To construct a profile of therapeutically actionable gene alterations in the major histological types of ovarian cancer, 72 Japanese patients with surgically resected ovarian cancers were selected from an original cohort consisting of 267 patients who had not received pre-treatment before surgery. Somatic mutations and copy number alterations at 740 hotspots in 46 cancer-related genes were detected by deep sequencing of genomic DNAs obtained from snap-frozen tumor tissues using a next generation sequencer. The alterations were verified by Sanger sequencing and quantitative genomic PCR. Mutations and/or copy number aberrations which will make tumors respond to molecular targeting drugs were detected in nine genes of 35/72 (48.6%) patients; PIK3CA (25.0%), KRAS (13.9%), ERBB2 (4.3%), PTEN (2.8%), RB1 (2.8%), CDKN2A (2.8%), AKT1 (1.4%), CTNNB1 (1.4%) and NRAS (1.4%). These mutations tended to occur in a mutually exclusive manner. Non-serous histological type tumors showed such actionable gene alterations frequently (32/47; 68.1%). Therefore, ovarian cancers, particularly of non-serous types, frequently carry gene aberrations that link to therapy using molecular targeting drugs.


Ovarian cancer is a leading cause of cancer mortality from gynecological malignancies worldwide and, in the United States and Japan, accounts for ~14,000 and 4,600 deaths annually (1,2). Ovarian cancer predominantly consists of four major histological types: serous, clear cell, endometrioid and mucinous adenocarcinomas. The incidence of each of these subtypes varies geographically: serous carcinoma is the most common type in Western and Asian countries; clear cell adenocarcinoma is prevalent (the second-most common) in Japan, but not in most of the other Asian countries, and is not prevalent in European countries (2,3). More than 70% of ovarian cancers are diagnosed as advanced stage cancers (3). The majority of these patients with advanced ovarian cancer show an initial response to platinum-based chemotherapy; however, most of these patients relapse (3). Consequently, the 5-year overall survival rate for ovarian cancer patients remains <50% (3). Personalized therapy using molecular targeting drugs based on gene aberrations in tumor cells is a promising option to improve the therapeutic efficacy of the treatment for advanced ovarian cancer (4).

Recent genome-wide analysis has revealed alterations of ovarian cancer genomes (58). The most frequent alterations found are inactivating mutations in tumor suppressor genes, such as TP53, PTEN, BRCA1, BRCA2, and RB1, and in a SWI/SNF chromatin remodeling gene, ARID1A. Other studies have detected activating mutations in the oncogenes KRAS, BRAF, PIK3CA and ERBB2, indicating that a subset of patients with ovarian cancer could benefit from therapy using existing molecular targeting drugs (57,911). However, the prevalence and specificity of such oncogene aberrations by clinicopathological factors, such as histological subtype, and whether the aberrations are present in a mutually exclusive manner, have not been fully examined in a defined population. Thus, we constructed a profile of actionable aberrations of 46 cancer-related genes in a cohort of 72 Japanese ovarian cancer patients. The cohort was chosen from 267 consecutive patients who had received surgery for ovarian cancer. Of these patients, 72 patients with ovarian cancer were surgically treated without prior chemotherapy, and the carcinomas in this cohort included all four histological tumor types and tumors at various stages.

Materials and methods

Patient cohort

Seventy-two patients with ovarian cancer (study cohort subjects) were selected from 267 consecutive patients with ovarian cancer (original cohort) who received surgery for ovarian cancer in the Department of Obstetrics and Gynecology, Jikei University School of Medicine, Tokyo, Japan, between 2000 and 2009. The 72 subjects were surgically treated patients with ovarian cancer who had not had prior chemotherapy. The selection procedure ensured that all four major histological types and stages of tumor were included in proportions similar to those found in the original cohort and were also representative of the proportions found in all Japanese ovarian cancer patients (Fig. 1) (2,3). Written informed consent was obtained from all patients. This study was approved by the Institutional Review Board of the contributing institutions.

The tumors and the adjacent non-cancerous tissues were macro-dissected and flash-frozen after surgery. All tumor tissues were resected from solid components without necrotic tissue in each tumor. Several tumor tissues were randomly selected for making paraffin sections and their cellularity was confirmed as being >80%.

Clinical information for each patient, including age, stage, histology, grade, residual tumor, treatment information, and survival time from primary surgery, was collected retrospectively. Tumors were staged in accordance with the International Federation on Gynecology and Obstetrics (FIGO) system. For each patient, the size of the residual tumor was recorded at the end of surgery. Tumors resistant to platinum-containing adjuvant chemotherapy (i.e., platinum resistance) were defined as those in patients who exhibited progression-free survival for <6 months after the completion of chemotherapy.

Cell lines

Fourteen ovarian cancer cell lines were used in this study. JHOC-5, JHOC-7, JHOC-8, and JHOC-9 were obtained from Riken BioResource Center (Tsukuba, Japan). HAC-2 was provided by Dr M. Nishida (Tsukuba University, Tsukuba, Japan). RMG-I and RMG-II were provided by Dr D. Aoki (Keio University, Tokyo, Japan). A2780 (undifferentiated carcinoma) was provided by Dr E. Reed (NCI, Bethesda, MD, USA) and 2008 was provided by Dr S.B. Howell (UCSD, San Diego, CA, USA). SKOV3, MCAS, TYK-nu, Ov-1063, and SW626 were obtained from ATCC (Rockville, MD, USA).

Deep sequencing of 46 cancer-related genes

Genomic DNA was extracted using a QIAamp DNA mini kit according to the manufacturer’s instructions (Qiagen, Limburg, The Netherlands). Purified genomic DNA obtained from tumor tissues and cell lines (10 ng) was used for the library construction using the Ion AmpliSeq Cancer primer pool (cat. no. 4471262, Life Technologies, Rockville, MD, USA) that targets 739 mutational hotspot regions of 46 cancer-related genes and, additionally, a set of custom primers for the E17K mutation hotspot in the AKT1 gene. Sequencing was run on the Ion Proton/PGM platform (Life Technologies). The median depth of coverage for aligned reads was 3,024 x (2,010–35,534) by map quality ≥20. Data analysis, including the hg19 human reference genome and variant calling, was carried out using the Torrent Suite Software v3.2 (Life Technologies).

Sanger sequencing

Genomic DNA (10 ng) was amplified by PCR using KAPA Taq DNA Polymerase (KAPA Biosystems, Woburn, MA, USA). PCR products were directly sequenced in both directions using the BigDye Termination kit and an ABI 3130xl DNA Sequencer (Applied Biosystems, Foster City, CA, USA).

Real-time genomic PCR

Copy number variations suggested by deep sequencing analysis were validated by real-time genomic PCR using a TaqMan Copy Number Assay and the ABI 7900HT real-time PCR system (Applied Biosystems). All TaqMan probes were purchased from Thermo Applied Biosystems: ERBB2 (ID Hs01932585_cn), PTEN (ID Hs05128032_cn), RB1 (ID Hs00331762_cn and a set of custom primers), TP53 (ID Hs06424630_cn), and FGFR1 (ID Hs02422066_cn) with RPPH1 (cat. no. 4403328) as a reference. Data were analyzed using ABI PRISM 7900HT Sequence Detection Software v2.3 for copy number analysis.

Statistical analysis

Statistical analyses were performed using JMP software (SAS Institute, New York, NY, USA). Associations of the gene alterations with clinicopathological factors were evaluated using Fisher’s exact test. For survival analysis, the Cox proportional hazard model was used for the univariate and multivariate analyses.


Profiling of aberrations in 46 cancer-related genes in 72 ovarian cancers

Clinical and histological characteristics of the study subjects are provided in Table I. The frequency of clear cell adenocarcinoma in this cohort was higher than that found in other countries, reflecting known prevalence of ovarian cancer in Japan (2,3).

Table I

Characteristics of 72 Japanese patients with ovarian cancer.

Table I

Characteristics of 72 Japanese patients with ovarian cancer.

Clinicopathological variablesNo. of patients with ovarian cancerFrequency (%)
 Clear cell2737
 Unknown/not graded3549
Residual tumor (cm)
Adjuvant chemotherapy
 Platinum + Taxane4563
 Platinum + Irinotecan1825
Platinum resistance
 Not evaluated913

We sequenced genomic DNAs from 72 ovarian cancer tissues, with a mean sequencing depth >2,000 in all cases, followed by Sanger sequencing validation (representative results in Fig. 2A). The results revealed 115 single-nucleotide variations (SNVs), but no insertions/deletions, at 740 hotspot sites in 46 cancer-related genes. The 115 SNVs were of 50 distinct types, and included 64 SNVs (43 types) that were deduced as somatic according to data from the Catalogue of Somatic Mutation in Cancer (COSMIC) database ( The somatic nature of these mutations was verified in some samples by Sanger sequencing of DNAs from corresponding non-cancerous tissues (Table II). In addition, another SNV detected in a single case, PIK3CA-N345H, caused an amino acid change in the PIK3CA protein, which is recurrently mutated in human cancers. Therefore, these 65 SNVs (44 types) were considered to represent somatic mutations. Furthermore, Sanger sequencing of DNAs from non-cancerous tissue revealed that the remaining 50 SNVs (six types) consisted of two missense mutations and 48 single-nucleotide polymorphisms (four types). Thus, in total, 67 somatic missense mutations (46 types) were detected in the study cohort (Table II).

Table II

Somatic SNVs detected in 72 patients with ovarian cancer.

Table II

Somatic SNVs detected in 72 patients with ovarian cancer.

GenePosition (ch: bp)Nucleotide changeAA changeCOSMIC IDVariant rate (%)SNV typeValidated as somatic changeMutated sample
TP5317: 7,579,882G31CE11QCOSM1160652.9Non-synonymousCT12
17: 7,579,358G329CR110PCOSM1125048.6Non-synonymousCT55
17: 7,578,535A395GK132RCOSM1158232.9Non-synonymousCT3
17: 7,578,534G396CK132NCOSM4396383.9Non-synonymousC, ST44
17: 7,578,526G404AC135YCOSM1080170.5Non-synonymousCT8
17: 7,578,461G469TV157FCOSM1067064.4Non-synonymousC, ST22
17: 7,578,454C476TA159VCOSM1114859.0Non-synonymousC, ST33
17: 7,578,406G524AR175HCOSM1064832.1–76.4Non-synonymousC, ST23, T50, T57, T59
17: 7,578,271A578TH193LCOSM1106658.5–73.2Non-synonymousC, ST16, T39
17: 7,578,269C580TL194FCOSM1099567.3Non-synonymousCT65
17: 7,578,263C586TR196XCOSM1070565.6Stop-gainC, ST48
17: 7,578,257G592TE198XCOSM4424150.8Stop-gainC, ST30
17: 7,578,212C637TR213XCOSM1065452.3Stop-gainC, ST21
17: 7,578,203G646AV216MCOSM1066771.8Non-synonymousCT13
17: 7,578,203G646TV216LCOSM1121081.3Non-synonymousC, ST67
17: 7,578,196T653GV218GCOSM4419871.5Non-synonymousCT43
17: 7,577,538G743AR248QCOSM1066276.1Non-synonymousCT46
17: 7,577,120G818AR273HCOSM1066051.1–67.1Non-synonymousCT49, T51
17: 7,577,114G824TC275FCOSM1070159.5Non-synonymousC, ST69
17: 7,577,106C832AP278TCOSM4369722.1Non-synonymousCT36
17: 7,577,094C844TR282WCOSM1070494.3Non-synonymousC, ST25
17: 7,577,022C916TR306XCOSM1066355.1Stop-gainCT58
17: 7,574,003C1024TR342XCOSM1107383.1Stop-gainCT68
PIK3CAa3: 178,916,876G263AR88QCOSM74632.5Non-synonymousCT14
3: 178,921,551A1033CN345H65.6Non-synonymousT45
3: 178,936,074C1616GP539RCOSM75945.5Non-synonymousC, ST71
3: 178,936,082G1624AE542KCOSM76010.1–22.2Non-synonymousC, ST6, T42, T57, T63
3: 178,936,091G1633AE545KCOSM76318.8–71.6Non-synonymousCT53, T60
3: 178,936,094C1636AQ546KCOSM76692.8–93.4Non-synonymousCT27, T28
3: 178,952,085A3140TH1047LCOSM77631.6Non-synonymousCT20
3: 178,952,085A3140GH1047RCOSM77512.5–42.4Non-synonymousC, ST4, T7, T11, T12, T35, T36
KRASa12: 25,398,284G35CG12ACOSM5226.8–22.1Non-synonymousCT15, T63
12: 25,398,284G35AG12DCOSM52129.1–95.7Non-synonymousC, ST10, T54, T72
12: 25,398,284G35TG12VCOSM5206.4–58.3Non-synonymousC, ST5, T29, T37, T58
12: 25,398,285G34CG12RCOSM51846.1Non-synonymousC, ST4
CDKN2Aa9: 21,971,161A197GH66RCOSM1425336.5Non-synonymousCT50
9: 21,971,203T155GM52RCOSM60843650.0Non-synonymousCT51
FGFR210: 123,279,677C755GS252WCOSM3690321.3Non-synonymousCT36
10: 123,258,036A1645CN549HCOSM25008338.7Non-synonymousC, ST14
PTENa10: 89,711,902T520GY174DCOSM2889773.6Non-synonymousCT20
10: 89,720,799T950GV317G41.9Non-synonymousST44
AKT1a14: 105,246,551G49AE17KCOSM3376523.0Non-synonymousCT11
CTNNB1a3: 41,266,103G100CG34RCOSM568416.8Non-synonymousCT31
KIT4: 55,593,464A1621CM541LCOSM2802656.2Non-synonymousCT2
MET7: 116,411,966T3005CV1002A52.2Non-synonymousST65
NRASa1: 115,258,747G35AG12DCOSM56460.4Non-synonymousCT20

a Actionable gene.

{ label (or @symbol) needed for fn[@id='tfn2-ijo-46-06-2389'] } S, somatic mutations confirmed by Sanger sequencing. C, somatic mutations validated in the COSMIC database.

TP53 (38.9%), PIK3CA (25.0%), and KRAS (13.9%) were the three most frequently mutated genes (Table III). The other genes in which mutations were found were PTEN, FGFR2, CDKN2A, AKT1, CTNNB1, NRAS, MET and KIT. The frequency of the TP53, PIK3CA and KRAS mutations were different in each histological subtype. TP53 was more frequently mutated in serous carcinomas (56.0%) than in the other subtypes (P=0.042 by Fisher’s exact test, compared with non-serous patients with ovarian cancer; 29.8%); PIK3CA was more frequently mutated in clear cell carcinomas (48.1%) than in the other subtypes (P<0.001 by Fisher’s exact test, compared with non-clear cell carcinoma patients; 11.1%), as previously indicated (7,10,1214). KRAS was more frequently mutated in clear cell carcinomas (25.9%) than in the other subtypes, consistent with previous reports (P=0.034 by Fisher’s exact test, compared with non-clear cell carcinoma patients; 6.7%) (9,10,1517).

Table III

SNVs and CNAs detected in 72 ovarian cancers.

Table III

SNVs and CNAs detected in 72 ovarian cancers.

No (%)

Type of alteration Gene/alterationTotal (n=72)Clear cell (n=27)Serous (n=25)Endometrioid (n=10)Mucinous (n=3)Others (n=7)
SNVTP5328 (38.9)5 (18.5)14 (56.0)2 (7.1)3 (100)4 (14.3)
PIK3CAa18 (25.0)13 (48.1)02 (20.0)1 (33.3)2 (28.6)
KRASa10 (13.9)7 (25.9)01 (10.0)02 (28.6)
PTENa2 (2.8)01 (4.0)1 (10.0)00
FGFR22 (2.8)1 (3.7)01 (10.0)00
CDKN2Aa2 (2.8)01 (4.0)01 (33.3)0
AKT1a1 (1.4)1 (3.7)0000
CTNNB1a1 (1.4)1 (3.7)0000
NRASa1 (1.4)001 (10.0)00
MET1 (1.4)001 (10.0)00
KIT1 (1.4)001 (10.0)00
CNAs ERBB2a/gain3 (4.3)001 (10.0)2 (67.7)0
RBa/homozygous deletion2 (2.8)1 (3.7)0001 (14.3)
PTENa/homozygous deletion1 (1.4)01 (4.0)000

a Actionable gene.

Copy number aberrations (CNAs) in the 46 genes were deduced by calculating the ratios of the sequence read fraction in each tumor compared to the sequence read fraction of a single non-cancerous tissue subjected to sequencing. Loci that were potentially affected were selected using the criteria of >2-times gains and <1/4-times losses (suggesting homozygous deletion), followed by verification with quantitative genomic PCR analysis (Fig. 2B). Ten CNAs in PTEN (1 case), RB1 (4 cases), TP53 (1 case), ERBB2 (3 cases) and FGFR1 (1 case) were suggested in 10 tumors, and six of them were confirmed by quantitative genomic PCR analysis; gains of the ERBB2 gene in three patients (4.2%); and homozygous deletions of the RB1 gene in two patients (2.8%) and of the PTEN gene in a patient (1.4%) (Table III).

Profile of cancer-related gene actionable alterations in the histological subtypes

A profile of therapeutically actionable alterations was next constructed (Fig. 2C). Genetic alterations, possibly affecting the gene function and sensitivity to existing therapeutic drugs or strategies, were selected here as actionable alterations. ERBB2 amplification is a well-known actionable alteration (1820). All the SNVs detected in the AKT1, CTNNB1, KRAS, PIK3CA and NRAS genes (31 SNVs in total) affected hotspot amino acids, and were considered actionable as targets for existing protein kinase inhibitors (2125). In addition, the SNVs found in the CDKN2A and PTEN genes, and the RB and PTEN homozygous deletions, were considered actionable as they are linked to responsiveness to several inhibitors (2628).

In total, 41 actionable gene alterations were detected in 35 of 72 (48.6%) patients (Fig. 3A). These mutations tended to exist in a mutually exclusive manner (Fig. 2C). In 30 of the 35 (85.7%) patients there was only one actionable alteration, while five patients had multiple alterations: one patient had mutations in three genes and four patients had mutations in two genes. In these five patients, fractions of mutant alleles were not evidently different between mutated genes, therefore, these mutations were likely to have occurred in similar fractions of cancer cells in each tissue. Of the different histological subtypes, clear cell carcinomas showed the highest frequency of actionable alterations (21/27; 77.8%), whereas serous carcinomas had the lowest frequency (3/25; 12.0%; Fig. 3B and C). This was largely due to the differential occurrence of PIK3CA mutations in the different histological subtypes (Fig. 2C). In non-serous carcinomas, the majority (32/47; 68.1%) had at least one actionable mutation (P<0.0001 by Fisher’s exact test, compared with serous carcinomas).

We proceeded to investigate the associations between the actionable alterations and clinicopathological factors (Fig. 4). However, we identified no significant associations between any of the actionable alterations and age, stage, differentiation grade, presence/absence of residual tumor, or therapeutic response to platinum therapy. Actionable gene alterations were not significantly associated with prognosis, either among all cases (data not shown) or among non-serous carcinomas in particular.


We constructed an actionable gene alteration profile of ovarian cancer of a Japanese population using the deep genome sequencing method. The majority (48.6%) of ovarian cancers, in particular non-serous carcinomas (68.1%), were found to carry at least one actionable alteration in the 46 cancer-related genes examined. The TP53, PIK3CA and KRAS genes were top three mutation genes. Consistent with previous reports (13,29), TP53 and PIK3CA were preferentially mutated in serous and clear cell carcinoma, respectively, while KRAS was preferentially mutated in clear cell carcinoma (Table III). Distinct molecular features of Japanese ovarian cancers were suggested. Frequency of KRAS mutation in clear cell carcinoma (25.9%) was higher than that in cases described previously (7%) (13), while frequency of hotspot TP53 mutations (57.8%) in high-grade serous carcinoma were less than that in Caucasian cases (>80%) (7,12). These results provide basic information for the understanding of ovarian carcinogenesis by different ethnicity.

According to this profile, therapeutic strategy using molecularly targeted drugs can be considered (Fig. 5). Tumors with PIK3CA, AKT1 and PTEN mutations, which cause activation of the PI3K-AKT-mTOR pathway, are targetable by PI3K/AKT/mTOR inhibitors (21,24,27). Indeed, the results of clinical trials have demonstrated that ovarian tumors with PIK3CA mutations exhibit a high response rate to these inhibitors (30). Tumors with ERBB2 amplification are targetable by ERBB2 inhibitors or antibodies, as evidenced by observations that ovarian cancer cases with ERBB2 amplification exhibit high response rates to an anti-ERBB2 antibody drug (20,31,32).

Tumors with KRAS and NRAS mutations can be targeted by MAPK inhibitors, although in many cancers therapeutic responses are less than expected based on clinical trials (33). Sorafenib, which targets RAF and other kinases and inhibits the RAS-RAF-ERK pathway, has been shown to be an effective treatment for two Japanese patients with recurrent ovarian clear cell carcinoma (34). Selumetinib, a MEK1/MEK2 inhibitor, significantly suppressed the growth of a mouse xenograft of a human ovarian clear cell adenocarcinoma (35). In addition, molecular targeted therapies for tumors with CTNNB1 mutations and CDKN2A inactivation have been indicated (22,28), while tumors with RB1 mutations are treatable by TORC inhibition based on synthetic lethality (28).

Importantly, the ability to prescribe a personalized therapy based on genetic alterations, guided by the single sequencing test described here, would be useful in clinical settings. Ovarian cancers in Japan include more non-serous cases than in other countries due to a higher fraction of clear cell cancers. Our study indicates that frequencies of the actionable alterations do not differ significantly by clinicopathological factors, therefore, analysis of all non-serous ovarian cancers at progressive stages will be an effective way to perform precision medicine of ovarian cancers based on actionable gene aberrations. In the strategy above, patients with serous ovarian cancers will not benefit from the therapy. However, recent studies have also suggested therapeutic approaches targeting p53 mutant proteins (36). Such approaches will benefit ovarian cancer patients with serous type ovarian cancer due to frequent TP53 mutations.

The present study has limitations. First, the utility of the above inhibitors has not been biologically proved. Gene aberration profiles for the same 46 genes were also obtained for 14 commonly used ovarian cancer cell lines (Table IV and Fig. 6). The results are consistent with those deposited in the COSMIC database ( PIK3CA and KRAS mutations are present in a subset of ovarian cancer cell lines, and consistent in vitro therapeutic responses by PI3K and MAPK inhibitors have been reported in a few cell lines (3537). However, cell lines with other infrequent alterations were not detected in these cell lines. Thus, more sets of cultured ovarian cancer cells are needed to investigate the therapeutic significance of such gene alterations. Second, tumor suppressor and chromatin remodeling genes that lack mutation hotspots but are actionable for synthetic lethality therapy were not examined in the present study: BRCA1, BRCA2 and ARID1A are examples (5,6,9). Tumors with BRCA1 and BRCA2 inactivation are susceptible to PARP1 inhibitors, while therapeutic strategies against tumors with ARID1A inactivation are also proposed (38,39). A more comprehensiveprofiling study including these genes are ongoing in our laboratory.

Table IV

SNVs detected in 14 ovarian cancer cell lines.

Table IV

SNVs detected in 14 ovarian cancer cell lines.

Sample nameGenePosition (ch: bp)Nucleotide changeAA changeVariant rate (%)SNV type
2008PIK3CA3: 178,936,091G1633AE545K47.9Non-synonymous
A2780ATM11: 108,123,551C1810TP604S25.7Non-synonymous
Hac2PIK3CA3: 178,952,085A3140GH1047R70.8Non-synonymous
JHOC7KIT4: 55,593,461G1606CV540L58.5Non-synonymous
JHOC7PIK3CA3: 178,936,082G1624AE542K35.8Non-synonymous
JHOC8FBXW74: 153,247,366G1196AR399Q75.3Non-synonymous
JHOC8KIT4: 55,593,464A1621CM541L99.8Non-synonymous
JHOC8TP5317: 7,578,406G524AR175H99.6Non-synonymous
JHOC9PIK3CA3: 178,936,082G1624AE542K96.1Non-synonymous
MCASKRAS12: 25,398,284G35AG12D80.7Non-synonymous
MCASPIK3CA3: 178,952,085A3140GH1047R48.2Non-synonymous
MCASSMAD418: 48,604,690T1512AS504R95.1Non-synonymous
OV-1063RB113: 49,037,903A2143TK715X99.2Stop-gain
OV-1063TP5317: 7,578,181C272TP91L22.0Non-synonymous
OV-1063TP5317: 7,577,118G820TV274F59.0Non-synonymous
RMG-1CDKN2A9: 21,971,184A217CS73R100.0Non-synonymous
SKOV-3FBXW74: 153,247,288G1274TR425L44.8Non-synonymous
SKOV-3PIK3CA3: 178,952,085A3140GH1047R46.0Non-synonymous
SW626KIT4: 55,593,464A1621CM541L48.3Non-synonymous
SW626KRAS12: 25,398,284G35TG12V51.0Non-synonymous
SW626SMAD418: 48,591,888G1051CD351H99.6Non-synonymous
TYK-nuKIT4: 55,593,464A1621CM541L99.6Stop-gain
TYK-nuNRAS1: 115,258,747G35AG12D33.7Non-synonymous
TYK-nuNRAS1: 115,256,530C181AQ61K63.5Non-synonymous
TYK-nuTP5317: 7,578,406G524AR175H99.3Non-synonymous


This study was supported by Grants-in-Aid from the Ministry of Health, Labor, and Welfare for Research for the 3rd Term Comprehensive 10-Year Strategy for Cancer Control and Promotion of Cancer Control Programs; and Extramural Collaborative Research Grant of Cancer Research Institute, Kanazawa University. M.T. and R.I. are awardees of the Research Resident Fellowship from the Foundation for Promotion of Cancer Research for the 3rd Term Comprehensive 10-Year Strategy for Cancer Control, Japan.



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Volume 46 Issue 6

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Takenaka M, Saito M, Iwakawa R, Yanaihara N, Saito M, Kato M, Ichikawa H, Shibata T, Yokota J, Okamoto A, Okamoto A, et al: Profiling of actionable gene alterations in ovarian cancer by targeted deep sequencing. Int J Oncol 46: 2389-2398, 2015
Takenaka, M., Saito, M., Iwakawa, R., Yanaihara, N., Saito, M., Kato, M. ... Kohno, T. (2015). Profiling of actionable gene alterations in ovarian cancer by targeted deep sequencing. International Journal of Oncology, 46, 2389-2398.
Takenaka, M., Saito, M., Iwakawa, R., Yanaihara, N., Saito, M., Kato, M., Ichikawa, H., Shibata, T., Yokota, J., Okamoto, A., Kohno, T."Profiling of actionable gene alterations in ovarian cancer by targeted deep sequencing". International Journal of Oncology 46.6 (2015): 2389-2398.
Takenaka, M., Saito, M., Iwakawa, R., Yanaihara, N., Saito, M., Kato, M., Ichikawa, H., Shibata, T., Yokota, J., Okamoto, A., Kohno, T."Profiling of actionable gene alterations in ovarian cancer by targeted deep sequencing". International Journal of Oncology 46, no. 6 (2015): 2389-2398.