References
- Renuse S, Chaerkady R, Pandey A. Proteogenomics. Proteomics. 2011;11(4):620–630.
- Vogel C, Marcotte EM. Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat Rev Genet. 2012;13(4):227–232.
- Pandey A, Mann M. Proteomics to study genes and genomes. Nature. 2000;405(6788):837–846.
- Yates JR 3rd, Eng JK, McCormack AL. Mining genomes: correlating tandem mass spectra of modified and unmodified peptides to sequences in nucleotide databases. Anal Chem. 1995;67(18):3202–3210.
- Pandey A, Lewitter F. Nucleotide sequence databases: a gold mine for biologists. Trends Biochem Sci. 1999;24(7):276–280.
- Jaffe JD, Berg HC, Church GM. Proteogenomic mapping as a complementary method to perform genome annotation. Proteomics. 2004;4(1):59–77.
- Kim MS, Pinto SM, Getnet D, et al. A draft map of the human proteome. Nature. 2014;509(7502):575–581.
- Tanner S, Shen Z, Ng J, et al. Improving gene annotation using peptide mass spectrometry. Genome Res. 2007;17(2):231–239.
- Desiere F, Deutsch EW, Nesvizhskii AI, et al. Integration with the human genome of peptide sequences obtained by high-throughput mass spectrometry. Genome Biol. 2004;6(1):R9.
- Brunner E, Ahrens CH, Mohanty S, et al. A high-quality catalog of the Drosophila melanogaster proteome. Nat Biotechnol. 2007;25(5):576–583.
- Merrihew GE, Davis C, Ewing B, et al. Use of shotgun proteomics for the identification, confirmation, and correction of C. elegans gene annotations. Genome Res. 2008;18(10):1660–1669.
- Castellana NE, Shen Z, He Y, et al. An automated proteogenomic method uses mass spectrometry to reveal novel genes in Zea mays. Mol Cell Proteomics. 2014;13(1):157–167.
- Prasad TS, Harsha HC, Keerthikumar S, et al. Proteogenomic analysis of Candida glabrata using high resolution mass spectrometry. J Proteome Res. 2012;11(1):247–260.
- Trapp J, Geffard O, Imbert G, et al. Proteogenomics of Gammarus fossarum to document the reproductive system of amphipods. Mol Cell Proteomics. 2014;13(12):3612–3625.
- Nirujogi RS, Pawar H, Renuse S, et al. Moving from unsequenced to sequenced genome: reanalysis of the proteome of Leishmania donovani. J Proteomics. 2014;97:48–61.
- Nagarajha Selvan LD, Kaviyil JE, Nirujogi RS, et al. Proteogenomic analysis of pathogenic yeast Cryptococcus neoformans using high resolution mass spectrometry. Clin Proteomics. 2014;11(1):5.
- Tomczak K, Czerwinska P, Wiznerowicz M. The cancer genome atlas (TCGA): an immeasurable source of knowledge. Contemp Oncol (Pozn). 2015;19(1A):A68–77.
- Hudson TJ, Anderson W, Artez A, et al. International network of cancer genome projects. Nature. 2010;464(7291):993–998.
- Maris JM. Recent advances in neuroblastoma. N Engl J Med. 2010;362(23):2202–2211.
- Ellis MJ, Gillette M, Carr SA, et al. Connecting genomic alterations to cancer biology with proteomics: the NCI clinical proteomic tumor analysis consortium. Cancer Discov. 2013;3(10):1108–1112.
- Helmy M, Sugiyama N, Tomita M, et al. Onco-proteogenomics: a novel approach to identify cancer-specific mutations combining proteomics and transcriptome deep sequencing. Genome Biol. 2010;11(Suppl 1):1–2.
- Zhang B, Wang J, Wang X, et al. Proteogenomic characterization of human colon and rectal cancer. Nature. 2014;513(7518):382–387.
- Halvey PJ, Wang X, Wang J, et al. Proteogenomic analysis reveals unanticipated adaptations of colorectal tumor cells to deficiencies in DNA mismatch repair. Cancer Res. 2014;74(1):387–397.
- Sheynkman GM, Shortreed MR, Frey BL, et al. Discovery and mass spectrometric analysis of novel splice-junction peptides using RNA-Seq. Mol Cell Proteomics. 2013;12(8):2341–2353.
- Wang X, Slebos RJ, Wang D, et al. Protein identification using customized protein sequence databases derived from RNA-Seq data. J Proteome Res. 2012;11(2):1009–1017.
- Menon R, Omenn GS. Proteomic characterization of novel alternative splice variant proteins in human epidermal growth factor receptor 2/neu-induced breast cancers. Cancer Res. 2010;70(9):3440–3449.
- Menon R, Zhang Q, Zhang Y, et al. Identification of novel alternative splice isoforms of circulating proteins in a mouse model of human pancreatic cancer. Cancer Res. 2009;69(1):300–309.
- Sun H, Xing X, Li J, et al. Identification of gene fusions from human lung cancer mass spectrometry data. BMC Genomics. 2013;14(Suppl 8):S5.
- Mo F, Hong X, Gao F, et al. A compatible exon-exon junction database for the identification of exon skipping events using tandem mass spectrum data. BMC Bioinformatics. 2008;9:537.
- Huang C-H, Kuo C-J, Liang S-S, et al. Onco-proteogenomics identifies urinary S100A9 and GRN as potential combinatorial biomarkers for early diagnosis of hepatocellular carcinoma. BBA Clinical. 2015;3:205–213.
- Gallien S, Duriez E, Domon B. Selected reaction monitoring applied to proteomics. J Mass Spectrom. 2011;46(3):298–312.
- Picotti P, Aebersold R. Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions. Nat Methods. 2012;9(6):555–566.
- Wang Q, Chaerkady R, Wu J, et al. Mutant proteins as cancer-specific biomarkers. Proc Natl Acad Sci U S A. 2011;108(6):2444–2449.
- Conlon KP, Basrur V, Rolland D, et al. Fusion peptides from oncogenic chimeric proteins as putative specific biomarkers of cancer. Mol Cell Proteomics. 2013;12(10):2714–2723.
- Rauniyar N. Parallel reaction monitoring: a targeted experiment performed using high resolution and high mass accuracy mass spectrometry. Int J Mol Sci. 2015;16(12):28566–28581.
- Stratton MR. Exploring the genomes of cancer cells: progress and promise. Science. 2011;331(6024):1553–1558.
- Wood LD, Parsons DW, Jones S, et al. The genomic landscapes of human breast and colorectal cancers. Science. 2007;318(5853):1108–1113.
- Jones S, Zhang X, Parsons DW, et al. Core signaling pathways in human pancreatic cancers revealed by global genomic analyses. Science. 2008;321(5897):1801–1806.
- Parsons DW, Jones S, Zhang X, et al. An integrated genomic analysis of human glioblastoma multiforme. Science. 2008;321(5897):1807–1812.
- Leiserson MD, Vandin F, Wu HT, et al. Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes. Nat Genet. 2015;47(2):106–114.
- Ruppen-Canas I, Lopez-Casas PP, Garcia F, et al. An improved quantitative mass spectrometry analysis of tumor specific mutant proteins at high sensitivity. Proteomics. 2012;12(9):1319–1327.
- Kriegsmann M, Arens N, Endris V, et al. Detection of KRAS, NRAS and BRAF by mass spectrometry - a sensitive, reliable, fast and cost-effective technique. Diagn Pathol. 2015;10:132.
- Altimari A, de Biase D, De Maglio G, et al. 454 next generation-sequencing outperforms allele-specific PCR, Sanger sequencing, and pyrosequencing for routine KRAS mutation analysis of formalin-fixed, paraffin-embedded samples. Onco Targets Ther. 2013;6:1057–1064.
- Slebos RJ, Wang X, Zhang B, et al. Proteomic analysis of colon and rectal carcinoma using standard and customized databases. Sci Data. 2015;2:150022.
- Woo S, Cha SW, Na S, et al. Proteogenomic strategies for identification of aberrant cancer peptides using large-scale next-generation sequencing data. Proteomics. 2014;14(23–24):2719–2730.
- Martelli PL, Fariselli P, Balzani E, et al. Predicting cancer-associated germline variations in proteins. BMC Genomics. 2012;13(Suppl 4):S8.
- Yang X, Lazar IM. XMAn: a Homo sapiens mutated-peptide database for the MS analysis of cancerous cell states. J Proteome Res. 2014;13(12):5486–5495.
- Mathivanan S, Ji H, Tauro BJ, et al., Identifying mutated proteins secreted by colon cancer cell lines using mass spectrometry. J Proteomics. 2012;76 Spec No:141–149.
- Li J, Duncan DT, Zhang B. CanProVar: a human cancer proteome variation database. Hum Mutat. 2010;31(3):219–228.
- Nam RK, Sugar L, Yang W, et al. Expression of the TMPRSS2:ERG fusion gene predicts cancer recurrence after surgery for localised prostate cancer. Br J Cancer. 2007;97(12):1690–1695.
- Leyten GH, Hessels D, Jannink SA, et al. Prospective multicentre evaluation of PCA3 and TMPRSS2-ERG gene fusions as diagnostic and prognostic urinary biomarkers for prostate cancer. Eur Urol. 2014;65(3):534–542.
- Grignani F, Ferrucci PF, Testa U, et al. The acute promyelocytic leukemia-specific PML-RAR alpha fusion protein inhibits differentiation and promotes survival of myeloid precursor cells. Cell. 1993;74(3):423–431.
- Yoshihara K, Wang Q, Torres-Garcia W, et al. The landscape and therapeutic relevance of cancer-associated transcript fusions. Oncogene. 2015;34(37):4845–4854. DOI:10.1038/onc.2014.406.
- Mertens F, Johansson B, Fioretos T, et al. The emerging complexity of gene fusions in cancer. Nat Rev Cancer. 2015;15(6):371–381.
- Leow PC, Ku C-S, Soo R, et al. Technological advances in the detection of novel fusion genes. eLS. 2012. DOI:10.1002/9780470015902.a0023916.
- Wu YC, Chang IC, Wang CL, et al. Comparison of IHC, FISH and RT-PCR methods for detection of ALK rearrangements in 312 non-small cell lung cancer patients in Taiwan. PLoS One. 2013;8(8):e70839.
- Grigoriou EE, Psarra KK, Garofalaki MK, et al. BCR-ABL fusion protein detection in peripheral blood and bone marrow samples of adult precursor B-cell acute lymphoblastic leukemia patients using the flow cytometric immunobead assay. Clin Chem Lab Med. 2012;50(9):1657–1663.
- Weerkamp F, Dekking E, Ng YY, et al. Flow cytometric immunobead assay for the detection of BCR-ABL fusion proteins in leukemia patients. Leukemia. 2009;23(6):1106–1117.
- Recchia AG, Caruso N, Bossio S, et al. Flow cytometric immunobead assay for detection of BCR-ABL1 fusion proteins in chronic myleoid leukemia: comparison with FISH and PCR techniques. PLoS One. 2015;10(6):e0130360.
- Dekking EH, van der Velden VH, Varro R, et al. Flow cytometric immunobead assay for fast and easy detection of PML-RARA fusion proteins for the diagnosis of acute promyelocytic leukemia. Leukemia. 2012;26(9):1976–1985.
- Liu L, Zhan P, Zhou X, et al. Detection of EML4-ALK in lung adenocarcinoma using pleural effusion with FISH, IHC, and RT-PCR methods. PLoS One. 2015;10(3):e0117032.
- Van Vlierberghe P, van Grotel M, Tchinda J, et al. The recurrent SET-NUP214 fusion as a new HOXA activation mechanism in pediatric T-cell acute lymphoblastic leukemia. Blood. 2008;111(9):4668–4680.
- Hessels D, Smit FP, Verhaegh GW, et al. Detection of TMPRSS2-ERG fusion transcripts and prostate cancer antigen 3 in urinary sediments may improve diagnosis of prostate cancer. Clin Cancer Res. 2007;13(17):5103–5108.
- Nguyen PN, Violette P, Chan S, et al. A panel of TMPRSS2:ERG fusion transcript markers for urine-based prostate cancer detection with high specificity and sensitivity. Eur Urol. 2011;59(3):407–414.
- Rostad K, Hellwinkel OJ, Haukaas SA, et al. TMPRSS2:ERG fusion transcripts in urine from prostate cancer patients correlate with a less favorable prognosis. Apmis. 2009;117(8):575–582.
- Kim P, Yoon S, Kim N, et al. ChimerDB 2.0–a knowledgebase for fusion genes updated. Nucleic Acids Res. 2010;38((Database issue)):D81–85.
- Matlin AJ, Clark F, Smith CW. Understanding alternative splicing: towards a cellular code. Nat Rev Mol Cell Biol. 2005;6(5):386–398.
- Caceres JF, Kornblihtt AR. Alternative splicing: multiple control mechanisms and involvement in human disease. Trends Genet. 2002;18(4):186–193.
- He C, Zhou F, Zuo Z, et al. A global view of cancer-specific transcript variants by subtractive transcriptome-wide analysis. PLoS One. 2009;4(3):e4732.
- Eswaran J, Horvath A, Godbole S, et al. RNA sequencing of cancer reveals novel splicing alterations. Sci Rep. 2013;3:1689.
- Matos P, Jordan P. Increased Rac1b expression sustains colorectal tumor cell survival. Mol Cancer Res. 2008;6(7):1178–1184.
- Yae T, Tsuchihashi K, Ishimoto T, et al. Alternative splicing of CD44 mRNA by ESRP1 enhances lung colonization of metastatic cancer cell. Nat Commun. 2012;3:883.
- Zhang F, Drabier R. SASD: the synthetic alternative splicing database for identifying novel isoform from proteomics. BMC Bioinformatics. 2013;14(Suppl 14):S13.
- Dunham I, Kundaje A, Aldred SF, et al. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489(7414):57–74.
- Cheetham SW, Gruhl F, Mattick JS, et al. Long noncoding RNAs and the genetics of cancer. Br J Cancer. 2013;108(12):2419–2425.
- Schmidt LH, Spieker T, Koschmieder S, et al. The long noncoding MALAT-1 RNA indicates a poor prognosis in non-small cell lung cancer and induces migration and tumor growth. J Thorac Oncol. 2011;6(12):1984–1992.
- Yang Z, Zhou L, Wu LM, et al. Overexpression of long non-coding RNA HOTAIR predicts tumor recurrence in hepatocellular carcinoma patients following liver transplantation. Ann Surg Oncol. 2011;18(5):1243–1250.
- Khaitan D, Dinger ME, Mazar J, et al. The melanoma-upregulated long noncoding RNA SPRY4-IT1 modulates apoptosis and invasion. Cancer Res. 2011;71(11):3852–3862.
- Dewaele B, Przybyl J, Quattrone A, et al. Identification of a novel, recurrent MBTD1-CXorf67 fusion in low-grade endometrial stromal sarcoma. Int J Cancer. 2014;134(5):1112–1122.
- Anderson DM, Anderson KM, Chang CL, et al. A micropeptide encoded by a putative long noncoding RNA regulates muscle performance. Cell. 2015;160(4):595–606.
- Bu D, Yu K, Sun S, et al. NONCODE v3.0: integrative annotation of long noncoding RNAs. Nucleic Acids Res. 2012;40(Database issue):D210–215.
- Balakirev ES, Ayala FJ. Pseudogenes: are they “junk” or functional DNA? Annu Rev Genet. 2003;37:123–151.
- Poliseno L, Salmena L, Zhang J, et al. A coding-independent function of gene and pseudogene mRNAs regulates tumour biology. Nature. 2010;465(7301):1033–1038.
- Kalyana-Sundaram S, Kumar-Sinha C, Shankar S, et al. Expressed pseudogenes in the transcriptional landscape of human cancers. Cell. 2012;149(7):1622–1634.
- Han L, Yuan Y, Zheng S, et al. The pan-cancer analysis of pseudogene expression reveals biologically and clinically relevant tumour subtypes. Nat Commun. 2014;5:3963.
- Pei B, Sisu C, Frankish A, et al. The GENCODE pseudogene resource. Genome Biol. 2012;13(9):R51.
- Imielinski M, Cha S, Rejtar T, et al. Integrated proteomic, transcriptomic, and biological network analysis of breast carcinoma reveals molecular features of tumorigenesis and clinical relapse. Mol Cell Proteomics. 2012;11(6):M111 014910.
- Cancer Genome Atlas Research Network. Comprehensive molecular characterization of gastric adenocarcinoma. Nature. 2014;513(7517):202–209. Doi:10.1038/nature13480
- Nesvizhskii AI. Proteogenomics: concepts, applications and computational strategies. Nat Methods. 2014;11(11):1114–1125.
- Li Y, Chi H, Wang LH, et al. Speeding up tandem mass spectrometry based database searching by peptide and spectrum indexing. Rapid Commun Mass Spectrom. 2010;24(6):807–814.
- Park CY, Klammer AA, Kall L, et al. Rapid and accurate peptide identification from tandem mass spectra. J Proteome Res. 2008;7(7):3022–3027.
- Diament BJ, Noble WS. Faster SEQUEST searching for peptide identification from tandem mass spectra. J Proteome Res. 2011;10(9):3871–3879.
- Branca RM, Orre LM, Johansson HJ, et al. HiRIEF LC-MS enables deep proteome coverage and unbiased proteogenomics. Nat Methods. 2014;11(1):59–62.
- Nagaraj SH, Waddell N, Madugundu AK, et al. PGTools: a software suite for proteogenomic data analysis and visualization. J Proteome Res. 2015;14(5):2255–2266.
- Savitski MM, Wi M, Hahne H, et al. A scalable approach for protein false discovery rate estimation in large proteomic data sets. Mol Cell Proteomics. 2015;14(9):2394–2404.
- Murtaza M, Dawson SJ, Tsui DW, et al. Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Nature. 2013;497(7447):108–112.
- Dawson SJ, Tsui DW, Murtaza M, et al. Analysis of circulating tumor DNA to monitor metastatic breast cancer. N Engl J Med. 2013;368(13):1199–1209.