Научная статья на тему 'Identification of BRCA1/2 mutations in breast cancer patients by next-generation sequencing'

Identification of BRCA1/2 mutations in breast cancer patients by next-generation sequencing Текст научной статьи по специальности «Клиническая медицина»

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Ключевые слова
BRCA1 / BRCA2 / breast cancer / NGS / DNA-sequencing / mutation / personalized medicine / BRCA1 / BRCA2 / рак молочной железы / NGS / ДНК-секвенирование / мутация / персонализированная медицина

Аннотация научной статьи по клинической медицине, автор научной работы — Stetsenko If, Krasnenko Ayu, Stanoevich Us, Mescheryakov Aa, Vorotnikov Ik

Breast cancer is one of the most widespread forms of solid tumors. By analyzing the traits of breast cancer pathogenesis at the molecular level using modern genetic analysis techniques and at different stages of the disease new data can be obtained to be further utilized in clinical practice. Molecular profiling based on next-generation sequencing is being increasingly applied as a clinical test to select target drugs for treating breast cancer patients with tumors highly resistant to therapy. In this study, we performed targeted sequencing of BRCA1 and BRCA2 oncogenes. In the total of 66 DNA samples from patients with breast tumors, BRCA1/2 mutations were found in 39 patients. There were 78 unique genetic variants, including 30 mutations in BRCA1 and 48 mutations in BRCA2. We identified 33 mutations affecting the sites of post-translational modification in proteins (PMT mutations).

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ИДЕНТИФИКАЦИЯ BRCA1/2-МУТАЦИЙ ПРИ РАКЕ МОЛОЧНОЙ ЖЕЛЕЗЫ С ПРИМЕНЕНИЕМ ТЕХНОЛОГИИ ВЫСОКОПРОИЗВОДИТЕЛЬНОГО СЕКВЕНИРОВАНИЯ

Рак молочной железы (РМЖ) является одной из наиболее распространенных форм солидных опухолей. Анализ особенностей патогенеза РМЖ на молекулярном уровне с применением современных методов генетического анализа и на разных стадиях заболевания позволяет получить новые данные для их дальнейшего применения в клинической практике. Молекулярное профилирование с применением технологий высокопроизводительного секвенирования все чаще применяют в качестве клинического теста при подборе таргетных препаратов для лечения пациентов с высокорезистентными к терапии опухолями при РМЖ. Целью работы было провести таргетное секвенирование генов BRCA1 и BRCA2 в составе панели онкогенов. Из 66 образцов ДНК пациентов с опухолями молочной железы, мутации BRCA1/2 обнаружены у 39 пацентов. Найдено 78 уникальных генетических вариантов, из них 30 мутаций в гене BRCA1 и 48 мутаций в гене BRCA2. Идентифицировано 33 мутации, оказывающие влияние на сайты посттрансляционной модификации белков (PMT-мутации).

Текст научной работы на тему «Identification of BRCA1/2 mutations in breast cancer patients by next-generation sequencing»

IDENTIFICATION OF BRCA1/2 MUTATIONS IN BREAST CANCER PATIENTS BY NEXT-GENERATION SEQUENCING

Stetsenko IF1, Krasnenko AYu1>2, Stanoevich US3, Mescheryakov AA4, Vorotnikov IK4, Druzhilovskaya OS1, Belova VA1, Churov AV1^

1 Vavilov Institute of General Genetics of the Russian Academy of Sciences, Moscow

2 Genotek Ltd., Moscow

3 Russian Scientific Center for X-ray Radiology of the Ministry of Health of the Russian Federation, Moscow

4 Blokhin Russian Cancer Research Centre, Moscow

5 IB KarRC RAS, Petrozavodsk

Breast cancer is one of the most widespread forms of solid tumors. By analyzing the traits of breast cancer pathogenesis at the molecular level using modern genetic analysis techniques and at different stages of the disease new data can be obtained to be further utilized in clinical practice. Molecular profiling based on next-generation sequencing is being increasingly applied as a clinical test to select target drugs for treating breast cancer patients with tumors highly resistant to therapy. In this study, we performed targeted sequencing of BRCA1 and BRCA2 oncogenes. In the total of 66 DNA samples from patients with breast tumors, BRCA1/2 mutations were found in 39 patients. There were 78 unique genetic variants, including 30 mutations in BRCA1 and 48 mutations in BRCA2. We identified 33 mutations affecting the sites of post-translational modification in proteins (PMT mutations).

Keywords: BRCA1, BRCA2, breast cancer, NGS, DNA-sequencing, mutation, personalized medicine

Funding: this work was supported by the Ministry of Education and Science of the Russian Federation (Project ID RFMEFI60716X0152).

EKI Correspondence should be addressed: Alexey V Churov Pushkinskaya 11, Petrozavodsk,185910; achurou@yandex.ru

Received: 03.12.2018 Accepted: 14.12.2018

DOI: 10.24075/brsmu.2018.074

ИДЕНТИФИКАЦИЯ BRCA1/2-МУТАЦИЙ ПРИ РАКЕ МОЛОЧНОЙ ЖЕЛЕЗЫ С ПРИМЕНЕНИЕМ ТЕХНОЛОГИИ ВЫСОКОПРОИЗВОДИТЕЛЬНОГО СЕКВЕНИРОВАНИЯ

И. Ф. Стеценко1, А. Ю. Красненко1,2, У. С. Станоевич3, А. А. Мещеряков4, И. К. Воротников4, О. С. Дружиловская1, В. А. Белова1, А. В. Чуров1^

1 Институт общей генетики имени Н. И. Вавилова РАН, Москва

2 ООО «Генотек», Москва

3 Российский научный центр рентгенорадиологии МЗ РФ, Москва

4 Национальный медицинский исследовательский центр онкологии имени Н. Н. Блохина, Москва

5 Институт биологии, Карельский научный центр (ИБ КарНЦ РАН), Петрозаводск

Рак молочной железы (РМЖ) является одной из наиболее распространенных форм солидных опухолей. Анализ особенностей патогенеза РМЖ на молекулярном уровне с применением современных методов генетического анализа и на разных стадиях заболевания позволяет получить новые данные для их дальнейшего применения в клинической практике. Молекулярное профилирование с применением технологий высокопроизводительного секвенирования все чаще применяют в качестве клинического теста при подборе таргетных препаратов для лечения пациентов с высокорезистентными к терапии опухолями при РМЖ. Целью работы было провести таргетное секвенирование генов BRCA1 и BRCA2 в составе панели онкогенов. Из 66 образцов ДНК пациентов с опухолями молочной железы, мутации BRCA1/2 обнаружены у 39 пацентов. Найдено 78 уникальных генетических вариантов, из них 30 мутаций в гене BRCA1 и 48 мутаций в гене BRCA2. Идентифицировано 33 мутации, оказывающие влияние на сайты посттрансляционной модификации белков (PMT-мутации).

Ключевые слова: BRCA1, BRCA2, рак молочной железы, NGS, ДНК-секвенирование, мутация, персонализированная медицина

Финансирование: работа выполнена при финансовой поддержке государства в лице Минобрнауки России (идентификатор соглашения RFMEFI60716X0152).

CxJ Для корреспонденции: Алексей Викторович Чуров

ул. Пушкинская, д. 11, г Петрозаводск, 185035; achurou@yandex.ru

Статья получена: 03.12.2018 Статья принята к печати: 14.12.2018

DOI: 10.24075/vrgmu.2018.074

Breast cancer (BC) is one of the most widespread forms of malignant neoplasms, next only to lung cancer and colorectal cancer. BC incidence has been growing in many parts of the world [1-4]. Early detection of the pathology and screening for BC is therefore a key task.

Suppressor genes BRCA1 and BRCA2 are important actors in regulating the signaling pathways associated with the functioning of DNA repair systems. Mutations in these genes entail an elevated risk of developing BC and some other forms of malignant tumors.

A substantial proportion of the mutations in tumors are somatic mutations, playing an important role both in the pathogenesis of sporadic BC and in the development of de novo resistance to anticancer drugs. Sporadic forms of cancer constitute, on average, 70-80% of BC cases, whereas only 10% of all the patients carry inherited mutations in the BRCA1 and BRCA2 genes [5].

The actual task of oncogenetics today is the development and improvement of approaches to the effective selection of anticancer drugs, taking into account the molecular-genetic features of tumor development.

The aim of this study was to identify the spectrum of mutations in the BRCA1 and BRCA2 genes in patients with BC by Illumina next-generation sequencing.

METHODS

Material for the study. Clinical characteristics of the patients

The collection of tumor samples for the study was taken from 66 patients with malignant breast neoplasms in hospital care at NN Blokhin National Medical Research Centre of Oncology of the Russian Health Ministry and Russian Scientific Center for X-ray Radiology of the Ministry of Health of the Russian Federation, (Moscow). The average age of the patients was 52.5 ± 9.7 years. The criteria for being included in the study were: age of 18 to 70, female, clinically verified BC diagnosis. Exclusion criteria: history of other forms of neoplasms, pregnancy. BC was staged according to TNM classification [6]. The study involved patients with stages T1-3N0-3M0-1. The study adhered to the principles of voluntariness and confidentiality. All patients provided informed consent to the study. The principal clinical characteristics of the patients are given in Table 1.

Table 1. Clinical characteristics of women with breast cancer (n = 66)

DNA isolation and quality control. Oncogene panel sequencing

Genomic DNA was isolated from tumor tissue samples by using DNeasy Blood and Tissue Kit (Qiagen; USA) as instructed by the manufacturer. The concentration of the extracted DNA specimens was measured with a Qubit 3.0 fluorometer (Thermo Fisher Scientific; USA). The quality of the DNA samples was additionally tested by electorphoresis in 1% agarose gel with ethidium bromide.

DNA fragment libraries were prepared using NEBNext Ultra DNA Library Prep Kit for Illumina (New England Biolabs; USA). The libraries were barcoded by PCR using two reagent kits: NEBNext Ultra DNA Library Prep Kit for Illumina and NEBNext Multiplex Oligos for Illumina (Dual Index Primers Set 1, New England Biolabs; USA). DNA library quality control was done by measurements with Agilent Bioanalyzer 2100 (Agilent Technologies; USA) using High Sensitivity Kit as instructed by the manufacturer.

Coding regions of the tumor genome were enriched using MYbaits Onconome KL v1.5 Panel (Mycroarray; USA). The analysis was performed with a high-throughput genome sequencing system HiSeq 2500 (Illumina; USA) using paired 100-nucleotide reads. The samples were prepared and initiated according to Illumina protocols.

Bioinformatic processing of NGS data

Bioinformatic processing of the resultant NGS data was carried out using a previously developed algorithm [7, 8]. At first, the quality of the reads from DNA sequencing was assessed by Cutadapt software, and they were mapped to the reference genome hg19 (GRCh37.p13) by using the BWA tool (Burrows-

Parameter Value, abs. no (%)

Age (years) 52.5 ± 9.7

Principal diagnosis:

Left breast cancer 32 (48.5)

Right breast cancer 32 (48.5)

Bilateral cancer 2 (3)

Tumor ^stage (TNM classification):

T1 36 (54.5)

T2 29 (43.9)

T3 1 (1.5)

Metastases in lymph nodes:

without metastases, M0 56 (84.8)

with metastases, M1 10 (15.2)

Expression of estrogen receptors (ER):

ER+ 53 (80.3)

ER- 13(19.7)

Expression of progesterone receptors (PR):

PR+ 50 (75.8)

PR- 16 (24.2)

Expression of HER2/neu (Cerb-B2):

Her2+ 38 (57.6)

Her2- 28 (42.4)

Note: the values are in M ± SD or % form; T 1-3 — tumor stages according to TNM classification; ER — estrogen receptor expression; PR — progesterone receptor expression; HER2/neu (Cerb-B2) — expression of the human epidermal growth factor receptor 2.

Wheeler Aligner). Paired reads were removed by running the specialized rmdup command in the SAMtools software package. Mutations in the NGS dataset were detected by MuTect, and DNA sequences covered by at least 12 readswere considered the most significant.

The mutation abundance was defined as the proportion (%) of mutation-supporing reads at a position. The functional effect of the mutations was assessed relying on ActiveDriverDB database [9]. The mutations affecting the coded protein were visualized using the ProteinPaint application [10].

RESULTS

We analyzed DNA samples from breast tumors (n = 66) for the presence of mutations in the BRCA1 and BRCA2 genes by Illumina next-generation sequencing. Bioinformatic processing of the NGS data revealed mutations in the BRCA1 and BRCA2

genes in 39 (59.1%) out of the 66 BC patients. Altogether 78 unique genetic variants were detected in the study, including 30 mutations in BRCA1 and 48 mutations in BRCA2. Among all these mutations, 70 of the detected variants were identified as new mutations (89.7%). All the detected genetic variants are listed in the Table 2.

The highest frequency in the analysis was demonstrated by the mutations 17:41246746:T>C in BRCA1 gene (52%) and 13:32914688:G>T in BRCA2 gene (47%). The mutation 13:32910800:A>C in BRCA2 gene occurred the most frequently among all samples, being identified in 10.7% (n = 3/28) of tumors with BRCA2 mutations. Mutations in both BRCA1 and BRCA2 were found in 11 patients with BC (16.7%; n = 66).

Annotation against databases revealed 33 mutations (42.3%) influencing the sequence of the coded protein, including 16 in BRCA1 gene and 17 in BRCA2 gene. The

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Fig. 1. The spectrum of mutations* affecting post-translational modification sites of proteins (PMT-mutations) in the genes BRCA1 (Â) and BRCA2 (B), in patients with breast cancer (n = 39). * — based on mutation effect prediction according to ActiveDriverDB

Table 2. BRCA1 and BRCA2 mutations identified in patients with BC

Gene Sample ID BC Stage The proportion of cancer cells in the sample1, % Variant allele frequency, % Coverage at the point PTM-mutation Effect2 Reference number2 Canonical designation

1 IIIA 20 52 235 No None Novel 17:41246746:T>C

2 IIA 9 30 117 No None rs1800744 17:41226488:C>A

4 106 No None Novel 17:41251858:T>G

3 IA 70 3 115 Yes distal Novel 17:41223236:T>G

2 267 Yes proximal Novel 17:41243968:T>G

1 439 No None Novel 17:41245560:C>A

4 I 30 4 116 Yes proximal rs80357088 (dbSNP) 17:41247872:C>A

1 685 Yes proximal rs80357192 (dbSNP) 17:41245428:C>T

5 IIA 8 4 230 Yes network-rewiring -motif loss Novel 17:41244256:G>C

6 I 90 2 169 Yes direct Novel 17:41244246:C>A

7 IIA 21 2 250 No None Novel 17:41244207:T>C

8 IA 8 2 306 No None Novel 17:41246576:A>C

9 IA 6 2 270 Yes distal Novel 17:41243724:A>C

2 142 Yes proximal Novel 17:41256210:T>G

BRCA1 10 IA 32 2 142 Yes distal Novel 17:41256225:T>G

1 333 Yes direct Novel 17:41246341:A>C

11 IIB 95 2 166 Yes proximal BRCA (TCGA MC3) 17:41243518:C>G

1 467 No None Novel 17:41245516:C>A

12 IA 98 1 202 Yes distal Novel 17:41247883:C>A

13 IA 15 1 660 Yes network-rewiring -motif loss Novel 17:41244951:C>A

14 IIB 35 1 444 No None Novel 17:41245785:C>A

15 I 12 1 569 No None Novel 17:41245228:C>T

16 IIB 12 1 351 No None Novel 17:41245832:T>G

17 IIA 57 1 413 No None Novel 17:41245859:C>A

18 IA 12 1 211 Yes proximal Novel 17:41226400:C>A

19 IIA 38 1 342 Yes distal rs786202665 (dbSNP) 17:41244544:T>C

20 IIA 32 1 307 No None Novel 17:41246752:C>A

21 IA 35 1 336 Yes distal Novel 17:41219637:C>A

1 379 No None Novel 17:41246125:T>A

22 IIA 10 1 390 No None Novel 17:41245026:C>A

9 IA 6 47 189 Yes distal Novel 13:32914688:G>T

2 210 Yes distal Novel 13:32905164:C>A

12 IA 98 6 471 No None rs28897716 (dbSNP) 13:32911295:G>A

1 434 Yes proximal Novel 13:32893381:A>C

23 IA 15 4 100 No None Novel 13:32906550:T>C

24 I 50 3 63 No None rs55924966 (dbSNP) 13:32929408:G>A

19 IIA 38 3 152 No None Novel 13:32912843:G>T

2 276 No None Novel 13:32912258:C>A

25 IA 65 2 319 No None Novel 13:32910800:A>C

BRCA2 14 IIB 35 2 316 Yes direct rs864622305 (dbSNP) 13:32900697:C>T

7 IIA 21 2 251 No None Novel 13:32944694:G>T

26 IA 10 2 255 No None Novel 13:32911260:A>T

1 537 No None Novel 13:32910800:A>C

27 IIA 11 2 87 Yes proximal Novel 13:32918761:C>A

2 238 No None Novel 13:32930703:C>A

28 IIA 70 2 130 No None Novel 13:32931930:G>T

1 307 Yes distal Novel 13:32914451:C>A

29 I 1 2 262 No None Novel 13:32910800:A>C

Note: 1 — based on histological data; 2 — based on ActiveDriverDB data (https://www.activedriverdb.org/).

End of Table 2

2 200 No None Novel 13:32911499:C>A

30 IIA 55 2 237 No None Novel 13:32913030:A>C

1 274 Yes distal Novel 13:32914261:C>A

2 99 Yes distal Novel 13:32893444:A>C

10 IA 32 2 179 No None Novel 13:32907009:T>G

2 188 Yes proximal Novel 13:32911946:T>G

2 807 No None Novel 13:32914484:C>A

1 323 No None Novel 13:32899216:G>A

4 I 30 1 747 No None Novel 13:32915036:A>T

1 279 No None Novel 13:32930596:T>A

1 285 No None Novel 13:32930604:A>G

21 IA 35 332 No None Novel 13:32914234:C>A

1 440 No None Novel 13:32907309:C>A

164 No None Novel 13:32912375:C>A

22 IIA 10 1 298 No None Novel 13:32907051:A>T

1 358 Yes distal Novel 13:32914844:G>A

2 IIA 9 165 No None Novel 13:32968849:T>C

31 IIIC 18 1 405 No None Novel 13:32913099:A>C

1 266 No None Novel 13:32929173:C>A

32 IIA 9 1 526 Yes proximal Novel 13:32913143:C>A

1 399 No None Novel 13:32968988:C>A

33 IIIA 10 1 233 Yes distal Novel 13:32911786:T>A

14 IA 15 1 362 No None Novel 13:32936764:C>A

34 IIA 14 1 371 Yes distal Novel 13:32912147:T>A

35 IB 5 1 246 No None Novel 13:32913558:C>T

1 434 Yes distal Novel 13:32914792:A>T

36 IIB 25 1 344 Yes distal Novel 13:32914433:G>A

37 IIB 80 1 569 Yes distal rs374326934 (dbSNP) 13:32914123:C>A

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1 275 No None Novel 13:32937605:G>A

1 IIIA 20 1 320 Yes distal Novel 13:32906966:A>G

38 I 10 1 439 No None Novel 13:32913444:C>A

39 IIA 18 1 262 No None Novel 13:32930600:C>A

1 363 No None Novel 13:32936793:C>A

mutations affecting the sites of post-translational modification in proteins (PMT mutations) are shown in the Fig. 1.

DISCUSSION

Personalized targeted therapy is gaining ground in modern oncology. The development of a highly sensitive and cost-efficient approach to affordable routine diagnosis of tumors is therefore a priority task.

The "gold standard" for mutation detection today is Sanger sequencing, but its diagnostic capabilities are limited compared to next-generation genetic analysis systems. Tumor cells are histologically and genetically heterogeneous, contributing to the advantage of NGS-based techniques, which allow developing efficient bioinformatics pipelines for detecting genetic variants both in pairs of tumor and normal tissues samples and within individual biopsies containing a fraction of normal cell DNA.

Mutations in the key BC oncogenes BRCA1 and BRCA2 are among the most frequent and significant molecular aberrations, whose analysis can help in assessing the risk of tumor development, clinical prediction for BC patients, and in predicting the effectivenesss of anticancer drug therapy.

The BRCA1 gene was identified by Y. Miki et al. in 1994 by positional cloning on the long arm of chromosome 17. The second gene — BRCA2, was mapped and isolated on chromosome 13q. BRCA1 and BRCA2 are suppressor genes, characterized by the autosomal dominant inheritance pattern and high penetrance. Recent molecular studies of BRCA1 and BRCA2 have demonstrated a wide spectrum of mutations present in these genes [5].

The international COSMIC database [11] contains over 900 somatic coding mutations of the BRCA1 gene and over 1400 coding mutations of the BRCA2 gene. A substantial part of these mutations result in structural transformations modifying

the function of protein products, thus undermining the capacity of repair systems to effectively fix DNA lesions. Many of the mutations in BRCA1/BRCA2 are missence mutations, where the coding sequence is altered and one functional codon is changed to another.

Having analyzed the NGS data for the BC tumors in our study by bioinformatics techniques, we identified 78 unique mutations in the genes BRCA1 and BRCA2. A majority of the mutations were found in BRCA2. According to the literature, the frequency of mutations differs notably between the genes BRCA1 and BRCA2 [5].

Further analysis using ActiveDriverDB showed that a large part of the genetic variants produce a functional effect on post-translational modification sites of the coded proteins (Fig. 1). Our study revealed 33 PMT-mutations, many of them previously unannotated. To confirm the pathogenic variants detected in the

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study and the status of the mutations, the research results need to be verified by Sanger sequencing using normal tissue samples.

CONCLUSIONS

Targeted next-generation sequencing appears to be the most promising approach for molecular profiling of tumors for clinical application. An integrated NGS-based analysis of mutations in the genes BRCA1 and BRCA2 in BC patients enables the identification of a greater number of mutations, including low mutant allele frequency variants, as well as genetic variants in biopsy samples with low tumor cell content. NGS-based approaches revealing mutations in the entire BRCA1 and BRCA2 coding sequence will enable a more effective identification of the patients to whom an adequate therapy with targeted anticancer drugs can be administered.

7. Cukanov KJu, Krasnenko AJu, Korostin DO, Churov AV, Stecenko IF, Plotnikov NA i dr. Rak molochnoj zhelezy: analiz spektra somaticheskih drajvernyh mutacij s primeneniem vysokoproizvoditel'nogo sekvenirovanija. Vestnik RGMU. 2017; (6): 52-8.

8. Cukanov KJu, Krasnenko AJu, Plahina DA, Korostin DO, Churov AV Druzhilovskaja O. S. i dr. Bioinformaticheskij protokol dlja obrabotki NGS-dannyh i identifikacii mutacij v solidnyh opuholjah cheloveka. Biomedicinskaja himija. 2017; 63 (5): 413-7.

9. Krassowski M, Paczkowska M, Cullion K, Huang T, Dzneladze I, Ouellette BFF et al. ActiveDriverDB: human disease mutations and genome variation in post-translational modification sites of proteins. Nucleic Acids Res. 2018; 46: D901-D910.

10. Zhou X, Edmonson MN, Wilkinson MR, Patel A, Wu G, Liu Y et al. Exploring genomic alteration in pediatric cancer using protein paint. Nat Genet. 2015; (48): 4-6.

11. Forbes SA, Beare D, Bindal N, Bamford S, Ward S, Cole CG et al. COSMIC: High-Resolution Cancer Genetics Using the Catalogue of Somatic Mutations in Cancer. Curr Protoc Hum Genet. 2016; (91): 10.11.1-10.11.37.

7. Цуканов К. Ю., Красненко А. Ю., Коростин Д. О., Чуров А. В., Стеценко И. Ф., Плотников Н. А. и др. Рак молочной железы: анализ спектра соматических драйверных мутаций с применением высокопроизводительного секвенирования. Вестник РГМУ. 2017; (6): 52-8.

8. Цуканов К. Ю., Красненко А. Ю., Плахина Д. А., Коростин Д. О., Чуров А. В., Дружиловская О. С. и др. Биоинформатический протокол для обработки NGS-данных и идентификации мутаций в солидных опухолях человека. Биомедицинская химия. 2017; 63 (5): 413-7.

9. Krassowski M, Paczkowska M, Cullion K, Huang T, Dzneladze I, Ouellette BFF et al. ActiveDriverDB: human disease mutations and genome variation in post-translational modification sites of proteins. Nucleic Acids Res. 2018; 46: D901-D910.

10. Zhou X, Edmonson MN, Wilkinson MR, Patel A, Wu G, Liu Y et al. Exploring genomic alteration in pediatric cancer using protein paint. Nat Genet. 2015; (48): 4-6.

11. Forbes SA, Beare D, Bindal N, Bamford S, Ward S, Cole CG et al. COSMIC: High-Resolution Cancer Genetics Using the Catalogue of Somatic Mutations in Cancer. Curr Protoc Hum Genet. 2016; (91): 10.11.1-10.11.37.

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