Biopolym. Cell. 2015; 31(6):436-446.
Genomics, Transcriptomics and Proteomics
NGS-based identification of druggable alterations and signaling pathways – hepatocellular carcinoma case report
1, 5Kotelnikova E. A., 1, 2Logacheva M. D., 2Nabieva E. R., 3, 5Pyatnitskiy M. A., 1, 5Vinogradov D. V., 2, 4, 5Makarova A. S., 5Demin A. V., 5Paleeva A. G., 5, 6Kremenetskaya O. S., 1, 2, 7Penin A. A., 1, 2Klepikova A. V., 2Kasianov A. S., 4Shavochkina D. A., 4Kudashkin N. E., 4Patyutko Yu. I., 2, 5Mugue N. S., 2Kondrashov A. S., 4, 7Lazarevich N. L
  1. A. A. Kharkevich Institute for Information Transmission Problems,
    19/1, Bolshoy Karetny per. Moscow, Russian Federation, 127051
  2. A. N. Belozersky Institute of Physico-Chemical Biology, M. V. Lomonosov Moscow State University
    Leninskie gory, house 1, building 40, Moscow, Russian Federation, 119992
  3. Orekhovich Institute of Biomedical Chemistry,
    10/8, Pogodinskaya Str., Moscow, Russian Federation, 119121
  4. N. N. Blokhin Russian Cancer Research Centre, RAMS
    24, Kashirskoye shosse, Moscow, Russian Federation, 115478
  5. ZAO Personal Biomedicine,
    124/17, Prospekt Mira, Moscow, Russian Federation, 129164
  6. Center for Theoretical Problems of Physicochemical Pharmacology RAS,
    4, Kosygin Str., Moscow, Russian Federation, 119991
  7. M. V. Lomonosov Moscow State University
    Leninskie Gory, 1/12, Moscow, Russian Federation, 119991


Aim. To identify potential cancer driving or clinically relevant molecular events for a patient with hepatocellular carcinoma. Methods. In order to achieve this goal, we performed RNA-seq and exome sequencing for the tumor tissue and its matched control. We annotated the alterations found using several publicly available databases and bioinformatics tools. Results. We identified several differentially expressed genes linked to the classical sorafenib treatment as well as additional pathways potentially druggable by therapies studied in clinical trials (Erlotinib, Lapatinib and Temsirolimus). Several germline mutations, found in XRCC1, TP53 and DPYD, according to the data from other clinical trials, could be related to the increased sensitivity to platinum therapies and reduced sensitivity to 5-Fluorouracil. We also identified several potentially driving mutations that could not be currently linked to therapies, like deletion in CIRBP, SNVs in BTG1, ERBB3, TCF7L2 et al. Conclusions. The presented study shows the potential usefulness of the integrated approach to the NGS data analysis, including the analysis of germline mutations and transcriptome in addition to the cancer panel or the exome sequencing data.
Keywords: NGS, cancer, systems biology, pathways, pharmacogenetics, personalized medicine


[1] Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144(5):646-74.
[2] Werner HM, Mills GB, Ram PT. Cancer Systems Biology: a peek into the future of patient care? Nat Rev Clin Oncol. 2014;11(3):167-76.
[3] Rodríguez-Antona C, Taron M. Pharmacogenomic biomarkers for personalized cancer treatment. J Intern Med. 2015;277(2):201-17.
[4] Mittal S, El-Serag HB. Epidemiology of hepatocellular carcinoma: consider the population. J Clin Gastroenterol. 2013;47 Suppl:S2-6.
[5] Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114-20.
[6] Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9(4):357-9.
[7] DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, Hartl C, Philippakis AA, del Angel G, Rivas MA, Hanna M, McKenna A, Fennell TJ, Kernytsky AM, Sivachenko AY, Cibulskis K, Gabriel SB, Altshuler D, Daly MJ. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet. 2011;43(5):491-8.
[8] Koboldt DC, Zhang Q, Larson DE, Shen D, McLellan MD, Lin L, Miller CA, Mardis ER, Ding L, Wilson RK. VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res. 2012;22(3):568-76.
[9] Wang K, Li M, Hakonarson H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010;38(16):e164.
[10] Reva B, Antipin Y, Sander C. Predicting the functional impact of protein mutations: application to cancer genomics. Nucleic Acids Res. 2011;39(17):e118.
[11] Adzhubei I, Jordan DM, Sunyaev SR. Predicting functional effect of human missense mutations using PolyPhen-2. Curr Protoc Hum Genet. 2013;Chapter 7:Unit7.20.
[12] Douville C, Carter H, Kim R, Niknafs N, Diekhans M, Stenson PD, Cooper DN, Ryan M, Karchin R. CRAVAT: cancer-related analysis of variants toolkit. Bioinformatics. 2013;29(5):647-8.
[13] Anders S, McCarthy DJ, Chen Y, Okoniewski M, Smyth GK, Huber W, Robinson MD. Count-based differential expression analysis of RNA sequencing data using R and Bioconductor. Nat Protoc. 2013;8(9):1765-86.
[14] Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol. 2010;11(10):R106.
[15] Höpfner M, Schuppan D, Scherübl H. Growth factor receptors and related signalling pathways as targets for novel treatment strategies of hepatocellular cancer. World J Gastroenterol. 2008;14(1):1-14.
[16] Davis AP, Grondin CJ, Lennon-Hopkins K, Saraceni-Richards C, Sciaky D, King BL, Wiegers TC, Mattingly CJ. The Comparative Toxicogenomics Database's 10th year anniversary: update 2015. Nucleic Acids Res. 2015;43(Database issue):D914-20.
[17] Kim YS, Jin HO, Seo SK, Woo SH, Choe TB, An S, Hong SI, Lee SJ, Lee KH, Park IC. Sorafenib induces apoptotic cell death in human non-small cell lung cancer cells by down-regulating mammalian target of rapamycin (mTOR)-dependent survivin expression. Biochem Pharmacol. 2011;82(3):216-26.
[18] Gedaly R, Angulo P, Hundley J, Daily MF, Chen C, Koch A, Evers BM. PI-103 and sorafenib inhibit hepatocellular carcinoma cell proliferation by blocking Ras/Raf/MAPK and PI3K/AKT/mTOR pathways. Anticancer Res. 2010;30(12):4951-8.
[19] Zeineldin R, Muller CY, Stack MS, Hudson LG. Targeting the EGF receptor for ovarian cancer therapy. J Oncol. 2010;2010:414676.
[20] Berasain C, Avila MA. The EGFR signalling system in the liver: from hepatoprotection to hepatocarcinogenesis. J Gastroenterol. 2014;49(1):9-23.
[21] Rouault JP, Rimokh R, Tessa C, Paranhos G, Ffrench M, Duret L, Garoccio M, Germain D, Samarut J, Magaud JP. BTG1, a member of a new family of antiproliferative genes. EMBO J. 1992;11(4):1663-70.
[22] Rodier A, Rochard P, Berthet C, Rouault JP, Casas F, Daury L, Busson M, Magaud JP, Wrutniak-Cabello C, Cabello G. Identification of functional domains involved in BTG1 cell localization. Oncogene. 2001;20(21):2691-703.
[23] Sun GG, Lu YF, Cheng YJ, Yang CR, Liu Q, Jing SW, Han XC. Expression of BTG1 in hepatocellular carcinoma and its correlation with cell cycles, cell apoptosis, and cell metastasis. Tumour Biol. 2014;35(12):11771-9.
[24] Lee HJ, Kang HJ, Kim KM, Yu ES, Kim KH, Kim SM, Kim TW, Shim JH, Lim YS, Lee HC, Chung YH, Lee YS. Fibroblast growth factor receptor isotype expression and its association with overall survival in patients with hepatocellular carcinoma. Clin Mol Hepatol. 2015;21(1):60-70.
[25] Whirl-Carrillo M, McDonagh EM, Hebert JM, Gong L, Sangkuhl K, Thorn CF, Altman RB, Klein TE. Pharmacogenomics knowledge for personalized medicine. Clin Pharmacol Ther. 2012;92(4):414-7.
[26] Offer SM, Wegner NJ, Fossum C, Wang K, Diasio RB. Phenotypic profiling of DPYD variations relevant to 5-fluorouracil sensitivity using real-time cellular analysis and in vitro measurement of enzyme activity. Cancer Res. 2013;73(6):1958-68.
[27] Huang ZH, Hua D, Li LH, Zhu JD. Prognostic role of p53 codon 72 polymorphism in gastric cancer patients treated with fluorouracil-based adjuvant chemotherapy. J Cancer Res Clin Oncol. 2008;134(10):1129-34.
[28] Zhang L, Ma W, Li Y, Wu J, Shi GY. Pharmacogenetics of DNA repair gene polymorphisms in non-small-cell lung carcinoma patients on platinum-based chemotherapy. Genet Mol Res. 2014;13(1):228-36.
[29] Pakakasama S, Kanchanakamhaeng K, Kajanachumpol S, Udomsubpayakul U, Sirachainan N, Thithapandha A, Hongeng S. Genetic polymorphisms of folate metabolic enzymes and toxicities of high dose methotrexate in children with acute lymphoblastic leukemia. Ann Hematol. 2007;86(8):609-11.
[30] Farrell JJ, Bae K, Wong J, Guha C, Dicker AP, Elsaleh H. Cytidine deaminase single-nucleotide polymorphism is predictive of toxicity from gemcitabine in patients with pancreatic cancer: RTOG 9704. Pharmacogenomics J. 2012;12(5):395-403.
[31] Sakano S, Hinoda Y, Sasaki M, Wada T, Matsumoto H, Eguchi S, Shinohara A, Kawai Y, Hara T, Nagao K, Hara T, Naito K, Matsuyama H. Nucleotide excision repair gene polymorphisms may predict acute toxicity in patients treated with chemoradiotherapy for bladder cancer. Pharmacogenomics. 2010;11(10):1377-87.
[32] Khrunin A, Ivanova F, Moisseev A, Khokhrin D, Sleptsova Y, Gorbunova V, Limborska S. Pharmacogenomics of cisplatin-based chemotherapy in ovarian cancer patients of different ethnic origins. Pharmacogenomics. 2012;13(2):171-8.
[33] Riedemann L, Lanvers C, Deuster D, Peters U, Boos J, Jürgens H, am Zehnhoff-Dinnesen A. Megalin genetic polymorphisms and individual sensitivity to the ototoxic effect of cisplatin. Pharmacogenomics J. 2008;8(1):23-8.