Applications of RNA Indexes for Precision Oncology in Breast Cancer

Marrone, 2015, Opportunities for translational epidemiology: the important role of observational studies to advance precision oncology, Cancer Epidemiol Biomarkers Prev, 24, 484, 10.1158/1055-9965.EPI-14-1086 Yu, 2016, Omics profiling in precision oncology, Mol Cell Proteomics, 15, 2525, 10.1074/mcp.O116.059253 Ahmed, 2016, Pharmacogenomics of drug metabolizing enzymes and transporters: relevance to precision medicine, Genomics Proteomics Bioinformatics, 14, 298, 10.1016/j.gpb.2016.03.008 Collins, 2015, A new initiative on precision medicine, N Engl J Med, 372, 793, 10.1056/NEJMp1500523 Hunter, 2016, Uncertainty in the era of precision medicine, N Engl J Med, 375, 711, 10.1056/NEJMp1608282 Cohen, 2014, From cancer genomics to precision oncology—tissue's still an issue, Cell, 157, 1509, 10.1016/j.cell.2014.05.027 Arnedos, 2015, Precision medicine for metastatic breast cancer—limitations and solutions, Nat Rev Clin Oncol, 12, 693, 10.1038/nrclinonc.2015.123 Biankin, 2015, Patient-centric trials for therapeutic development in precision oncology, Nature, 526, 361, 10.1038/nature15819 Roychowdhury, 2016, Translating cancer genomes and transcriptomes for precision oncology, CA Cancer J Clin, 66, 75, 10.3322/caac.21329 Senft, 2017, Precision oncology: the road ahead, Trends Mol Med, 23, 874, 10.1016/j.molmed.2017.08.003 Chen, 2017, Characterizing and annotating the genome using RNA-seq data, Sci China Life Sci, 60, 116, 10.1007/s11427-015-0349-4 Sestak, 2015, Update on breast cancer risk prediction and prevention, Curr Opin Obstet Gynecol, 27, 92, 10.1097/GCO.0000000000000153 Ellis, 2015, Selective estrogen receptor modulators in clinical practice: a safety overview, Expert Opin Drug Saf, 14, 921, 10.1517/14740338.2015.1014799 Lumachi, 2015, Current medical treatment of estrogen receptor-positive breast cancer, World J Biol Chem, 6, 231, 10.4331/wjbc.v6.i3.231 Gradishar, 2012, HER2 therapy — an abundance of riches, N Engl J Med, 366, 176, 10.1056/NEJMe1113641 Figueroa-Magalhães, 2014, Treatment of HER2-positive breast cancer, Breast, 23, 128, 10.1016/j.breast.2013.11.011 Foulkes, 2010, Triple-negative breast cancer, N Engl J Med, 363, 1938, 10.1056/NEJMra1001389 Hurvitz, 2016, Triple-negative breast cancer: advancements in characterization and treatment approach, Curr Opin Obstet Gynecol, 28, 59 Lehmann, 2014, Identification and use of biomarkers in treatment strategies for triple-negative breast cancer subtypes, J Pathol, 232, 142, 10.1002/path.4280 Hirshfield, 2014, Triple-negative breast cancer: molecular subtypes and targeted therapy, Curr Opin Obstet Gynecol, 26, 34, 10.1097/GCO.0000000000000038 Judes, 2016, High-throughput «Omics» technologies: new tools for the study of triple-negative breast cancer, Cancer Lett, 382, 77, 10.1016/j.canlet.2016.03.001 Jia, 2016, Potential role of targeted therapies in the treatment of triple-negative breast cancer, Anticancer Drugs, 27, 147, 10.1097/CAD.0000000000000328 Ding, 2010, Genome remodelling in a basal-like breast cancer metastasis and xenograft, Nature, 464, 999, 10.1038/nature08989 Banerji, 2012, Sequence analysis of mutations and translocations across breast cancer subtypes, Nature, 486, 405, 10.1038/nature11154 The Cancer Genome Atlas Network, 2012, Comprehensive molecular portraits of human breast tumours, Nature, 490, 61, 10.1038/nature11412 Popova, 2012, Ploidy and large-scale genomic instability consistently identify basal-like breast carcinomas with BRCA1/2 inactivation, Cancer Res, 72, 5454, 10.1158/0008-5472.CAN-12-1470 Shah, 2012, The clonal and mutational evolution spectrum of primary triple-negative breast cancers, Nature, 486, 395, 10.1038/nature10933 Curtis, 2012, The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups, Nature, 486, 346, 10.1038/nature10983 Michailidou, 2013, Large-scale genotyping identifies 41 new loci associated with breast cancer risk, Nat Genet, 45, 353, 10.1038/ng.2563 Alexandrov, 2013, Signatures of mutational processes in human cancer, Nature, 500, 415, 10.1038/nature12477 Chen, 2014, Identification of causal genetic drivers of human disease through systems-level analysis of regulatory networks, Cell, 159, 402, 10.1016/j.cell.2014.09.021 Foedermayr, 2014, BRCA-1 methylation and TP53 mutation in triple-negative breast cancer patients without pathological complete response to taxane-based neoadjuvant chemotherapy, Cancer Chemother Pharmacol, 73, 771, 10.1007/s00280-014-2404-1 Burstein, 2015, Comprehensive genomic analysis identifies novel subtypes and targets of triple-negative breast cancer, Clin Cancer Res, 21, 1688, 10.1158/1078-0432.CCR-14-0432 Michailidou, 2015, Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer, Nat Genet, 47, 373, 10.1038/ng.3242 Gao, 2016, Punctuated copy number evolution and clonal stasis in triple-negative breast cancer, Nat Genet, 48, 1119, 10.1038/ng.3641 Nik-Zainal, 2016, Landscape of somatic mutations in 560 breast cancer whole-genome sequences, Nature, 534, 47, 10.1038/nature17676 Pereira, 2016, The somatic mutation profiles of 2,433 breast cancers refine their genomic and transcriptomic landscapes, Nature Commun, 7, 11479, 10.1038/ncomms11479 Yates, 2017, Genomic evolution of breast cancer metastasis and relapse, Cancer Cell, 32, 169, 10.1016/j.ccell.2017.07.005 Michailidou, 2017, Association analysis identifies 65 new breast cancer risk loci, Nature, 551, 92, 10.1038/nature24284 Zehir, 2017, Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients, Nat Med, 23, 703, 10.1038/nm.4333 Martin, 2017, Discovery of naturally occurring ESR1 mutations in breast cancer cell lines modelling endocrine resistance, Nat Commun, 8, 1865, 10.1038/s41467-017-01864-y Polak, 2017, A mutational signature reveals alterations underlying deficient homologous recombination repair in breast cancer, Nat Genet, 49, 1476, 10.1038/ng.3934 Rheinbay, 2017, Recurrent and functional regulatory mutations in breast cancer, Nature, 547, 55, 10.1038/nature22992 Kamel, 2017, Exploitation of gene expression and cancer biomarkers in paving the path to era of personalized medicine, Genomics Proteomics Bioinformatics, 15, 220, 10.1016/j.gpb.2016.11.005 McGee, 2017, Network analysis reveals a signaling regulatory loop in PIK3CA-mutated breast cancer predicting survival outcome, Genomics Proteomics Bioinformatics, 15, 121, 10.1016/j.gpb.2017.02.002 Easton, 2007, Genome-wide association study identifies novel breast cancer susceptibility loci, Nature, 447, 1087, 10.1038/nature05887 Hunter, 2007, A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer, Nat Genet, 39, 870, 10.1038/ng2075 Haiman, 2011, A common variant at the TERT-CLPTM1L locus is associated with estrogen receptor–negative breast cancer, Nat Genet, 43, 1210, 10.1038/ng.985 Siddiq, 2012, Lindstro¨m S, Eccles D, Millikan RC. A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11, Hum Mol Genet, 21, 5373, 10.1093/hmg/dds381 Ghoussaini, 2012, Genome-wide association analysis identifies three new breast cancer susceptibility loci, Nat Genet, 44, 312, 10.1038/ng.1049 Liu, 2017, Identification of breast cancer associated variants that modulate transcription factor binding, PLoS Genet, 13, e1006761, 10.1371/journal.pgen.1006761 Shi, 2017, Differential expression profiles of the transcriptome in breast cancer cell lines revealed by next generation sequencing, Cell Physiol Biochem, 44, 804, 10.1159/000485344 Casamassimi, 2017, Transcriptome profiling in human diseases: new advances and perspectives, Int J Mol Sci, 18, 1652, 10.3390/ijms18081652 Liu, 2008, MicroRNA expression profiling using microarrays, Nat Protoc, 3, 563, 10.1038/nprot.2008.14 Yin, 2008, Profiling microRNA expression with microarrays, Trends Biotechnol, 26, 70, 10.1016/j.tibtech.2007.11.007 Chen, 2009, Reproducibility of quantitative RT-PCR array in miRNA expression profiling and comparison with microarray analysis, BMC Genomics, 10, 407, 10.1186/1471-2164-10-407 Sørlie, 2001, Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications, Proc Natl Acad Sci U S A, 98, 10869, 10.1073/pnas.191367098 Hu, 2006, The molecular portraits of breast tumors are conserved across microarray platforms, BMC Genomics, 7, 96, 10.1186/1471-2164-7-96 Parker, 2009, Supervised risk predictor of breast cancer based on intrinsic subtypes, J Clin Oncol, 27, 1160, 10.1200/JCO.2008.18.1370 Hu, 2009, Genetic alterations and oncogenic pathways associated with breast cancer subtypes, Mol Cancer Res, 7, 511, 10.1158/1541-7786.MCR-08-0107 Hollestelle, 2010, Distinct gene mutation profiles among luminal-type and basal-type breast cancer cell lines, Breast Cancer Res Treat, 121, 53, 10.1007/s10549-009-0460-8 Castaneda, 2012, Behaviour of breast cancer molecular subtypes through tumour progression, Clin Transl Oncol, 14, 481, 10.1007/s12094-012-0827-x Engstrøm, 2013, Molecular subtypes, histopathological grade and survival in a historic cohort of breast cancer patients, Breast Cancer Res Treat, 140, 463, 10.1007/s10549-013-2647-2 Kimbung, 2015, Contrasting breast cancer molecular subtypes across serial tumor progression stages: biological and prognostic implications, Oncotarget, 6, 33306, 10.18632/oncotarget.5089 Chen, 2015, Microarray expression profiling of dysregulated long non-coding RNAs in triple-negative breast cancer, Cancer Biol Ther, 16, 856, 10.1080/15384047.2015.1040957 Karagoz, 2015, Triple negative breast cancer: a multi-omics network discovery strategy for candidate targets and driving pathways, OMICS, 19, 115, 10.1089/omi.2014.0135 Jiang, 2016, Transcriptome analysis of triple-negative breast cancer reveals an integrated mRNA-lncRNA signature with predictive and prognostic value, Cancer Res, 76, 2105, 10.1158/0008-5472.CAN-15-3284 Liu, 2016, Comprehensive transcriptome profiling reveals multigene signatures in triple-negative breast cancer, Clin Cancer Res, 22, 1653, 10.1158/1078-0432.CCR-15-1555 Peng, 2017, Integrated analysis of differentially expressed genes and pathways in triple-negative breast cancer, Mol Med Rep, 15, 1087, 10.3892/mmr.2017.6101 Wang, 2009, RNA-Seq: a revolutionary tool for transcriptomics, Nat Rev Genet, 10, 57, 10.1038/nrg2484 Costa, 2010, Uncovering the complexity of transcriptomes with RNA-Seq, J Biomed Biotechnol, 2010, 853916, 10.1155/2010/853916 Metzker, 2010, Sequencing technologies–the next generation, Nat Rev Genet, 11, 31, 10.1038/nrg2626 Costa, 2013, RNA-Seq and human complex diseases: recent accomplishments and future perspectives, Eur J Hum Genet, 21, 134, 10.1038/ejhg.2012.129 van Dijk, 2014, Ten years of next-generation sequencing technology, Trends Genet, 30, 418, 10.1016/j.tig.2014.07.001 Edgren, 2011, Identification of fusion genes in breast cancer by paired-end RNA-sequencing, Genome Biol, 12, R6, 10.1186/gb-2011-12-1-r6 Ha, 2011, Identification of gene fusion transcripts by transcriptome sequencing in BRCA1-mutated breast cancers and cell lines, BMC Med Genomics, 4, 75, 10.1186/1755-8794-4-75 Kim, 2015, Recurrent fusion transcripts detected by whole-transcriptome sequencing of 120 primary breast cancer samples, Genes Chromosomes Cancer, 54, 681, 10.1002/gcc.22279 Kumar-Sinha, 2015, Landscape of gene fusions in epithelial cancers: seq and ye shall find, Genome Med, 7, 129, 10.1186/s13073-015-0252-1 Veeraraghavan, 2016, Recurrent and pathological gene fusions in breast cancer: current advances in genomic discovery and clinical implications, Breast Cancer Res Treat, 158, 219, 10.1007/s10549-016-3876-y Buermans, 2010, New methods for next generation sequencing based microRNA expression profiling, BMC Genomics, 11, 716, 10.1186/1471-2164-11-716 Pritchard, 2012, MicroRNA profiling: approaches and considerations, Nat Rev Genet, 13, 358, 10.1038/nrg3198 Lehmann, 2011, Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies, J Clin Invest, 121, 2750, 10.1172/JCI45014 Eswaran, 2012, Transcriptomic landscape of breast cancers through mRNA sequencing, Sci Rep, 2, 264, 10.1038/srep00264 Abramson, 2015, Subtyping of triple-negative breast cancer: implications for therapy, Cancer, 121, 8, 10.1002/cncr.28914 Le Du, 2015, Is the future of personalized therapy in triple-negative breast cancer based on molecular subtype?, Oncotarget, 6, 12890, 10.18632/oncotarget.3849 Kalimutho, 2015, Targeted therapies for triple-negative breast cancer: combating a stubborn disease, Trends Pharmacol Sci, 36, 822, 10.1016/j.tips.2015.08.009 Liu, 2016, Comprehensive transcriptome analysis identifies novel molecular subtypes and subtype-specific RNAs of triple-negative breast cancer, Breast Cancer Res, 18, 33, 10.1186/s13058-016-0690-8 Andreopoulou, 2017, Therapeutic advances and new directions for triple-negative breast cancer, Breast Care (Basel), 12, 21, 10.1159/000455821 Mayer, 2014, New strategies for triple-negative breast cancer-deciphering the heterogeneity, Clin Cancer Res, 20, 782, 10.1158/1078-0432.CCR-13-0583 McLornan, 2014, Applying synthetic lethality for the selective targeting of cancer, N Engl J Med, 371, 1725, 10.1056/NEJMra1407390 Jerby-Arnon, 2014, Predicting cancer-specific vulnerability via data-driven detection of synthetic lethality, Cell, 158, 1199, 10.1016/j.cell.2014.07.027 Rios, 2011, PARP inhibitors in breast cancer: BRCA and beyond, Oncology (Williston Park), 25, 1014 Arun, 2015, The PARP inhibitor AZD2281 (Olaparib) induces autophagy/mitophagy in BRCA1 and BRCA2 mutant breast cancer cells, Int J Oncol, 47, 262, 10.3892/ijo.2015.3003 Livraghi, 2015, PARP inhibitors in the management of breast cancer: current data and future prospects, BMC Med, 13, 188, 10.1186/s12916-015-0425-1 McDonald, 2017, Project DRIVE: a compendium of cancer dependencies and synthetic lethal relationships uncovered by large-scale, deep RNAi screening, Cell, 170, 577, 10.1016/j.cell.2017.07.005 Bauer, 2010, RNA interference (RNAi) screening approach identifies agents that enhance paclitaxel activity in breast cancer cells, Breast Cancer Res, 12, R41, 10.1186/bcr2595 Kourtidis, 2010, An RNA interference screen identifies metabolic regulators NR1D1 and PBP as novel survival factors for breast cancer cells with the ERBB2 signature, Cancer Res, 70, 1783, 10.1158/0008-5472.CAN-09-1550 Boimel, 2011, A functional in vivo screen for regulators of tumor progression identifies HOXB2 as a regulator of tumor growth in breast cancer, Genomics, 98, 164, 10.1016/j.ygeno.2011.05.011 Marotta, 2011, The JAK2/STAT3 signaling pathway is required for growth of CD44+CD24- stem cell-like breast cancer cells in human tumors, J Clin Invest, 121, 2723, 10.1172/JCI44745 Boyer, 2013, Quantitative proteomics with siRNA screening identifies novel mechanisms of Trastuzumab resistance in HER2 amplified breast cancers, Mol Cell Proteomics, 12, 180, 10.1074/mcp.M112.020115 Mahmood, 2014, A siRNA screen identifies RAD21, EIF3H, CHRAC1 and TANC2 as driver genes within the 8q23, 8q24.3 and 17q23 amplicons in breast cancer with effects on cell growth, survival and transformation, Carcinogenesis, 35, 670, 10.1093/carcin/bgt351 Garcia-Murillas, 2014, An siRNA screen identifies the GNAS locus as a driver in 20q amplified breast cancer, Oncogene, 33, 2478, 10.1038/onc.2013.202 Brough, 2011, Functional viability profiles of breast cancer, Cancer Discov, 1, 260, 10.1158/2159-8290.CD-11-0107 Marcotte, 2012, Essential gene profiles in breast, pancreatic, and ovarian cancer cells, Cancer Discov, 2, 172, 10.1158/2159-8290.CD-11-0224 Giamas, 2011, Kinome screening for regulators of the estrogen receptor identifies LMTK3 as a new therapeutic target in breast cancer, Nat Med, 17, 715, 10.1038/nm.2351 Hu, 2012, Small interfering RNA library screen identified polo-like kinase-1 (PLK1) as a potential therapeutic target for breast cancer that uniquely eliminates tumor-initiating cells, Breast Cancer Res, 14, R22, 10.1186/bcr3107 Petrocca, 2013, A genome-wide siRNA screen identifies proteasome addiction as a vulnerability of basal-like triple-negative breast cancer cells, Cancer Cell, 24, 182, 10.1016/j.ccr.2013.07.008 Garimella, 2014, Identification of novel molecular regulators of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL)-induced apoptosis in breast cancer cells by RNAi screening, Breast Cancer Res, 16, R41, 10.1186/bcr3645 Deng, 2014, shRNA kinome screen identifies TBK1 as a therapeutic target for HER2+ breast cancer, Cancer Res, 74, 2119, 10.1158/0008-5472.CAN-13-2138 Bhola, 2015, Kinome-wide functional screen identifies role of PLK1 in hormone-independent, ER-positive breast cancer, Cancer Res, 75, 405, 10.1158/0008-5472.CAN-14-2475 van Roosmalen, 2015, Tumor cell migration screen identifies SRPK1 as breast cancer metastasis determinant, J Clin Invest, 125, 1648, 10.1172/JCI74440 Marcotte, 2016, Functional genomic landscape of human breast cancer drivers, vulnerabilities, and resistance, Cell, 164, 293, 10.1016/j.cell.2015.11.062 Campbell, 2016, Large-scale profiling of kinase dependencies in cancer cell lines, Cell Rep, 14, 2490, 10.1016/j.celrep.2016.02.023 Horiuchi, 2016, PIM1 kinase inhibition as a targeted therapy against triple-negative breast tumors with elevated MYC expression, Nat Med, 22, 1321, 10.1038/nm.4213 Workenhe, 2016, Genome-wide lentiviral shRNA screen identifies serine/arginine-rich splicing factor 2 as a determinant of oncolytic virus activity in breast cancer cells, Oncogene, 35, 2465, 10.1038/onc.2015.303 Carninci, 2007, Noncoding RNA transcription beyond annotated genes, Curr Opin Genet Dev, 17, 139, 10.1016/j.gde.2007.02.008 Bartel, 2004, MicroRNAs: genomics, biogenesis, mechanism, and function, Cell, 116, 281, 10.1016/S0092-8674(04)00045-5 Nilsen, 2007, Mechanisms of microRNA-mediated gene regulation in animal cells, Trends Genet, 23, 243, 10.1016/j.tig.2007.02.011 Dvinge, 2013, The shaping and functional consequences of the microRNA landscape in breast cancer, Nature, 497, 378, 10.1038/nature12108 Riaz, 2013, miRNA expression profiling of 51 human breast cancer cell lines reveals subtype and driver mutation-specific miRNAs, Breast Cancer Res, 15, R33, 10.1186/bcr3415 Gyparaki, 2014, MicroRNAs as regulatory elements in triple negative breast cancer, Cancer Lett, 354, 1, 10.1016/j.canlet.2014.07.036 Sui, 2015, MicroRNAs-mediated cell fate in triple negative breast cancers, Cancer Lett, 361, 8, 10.1016/j.canlet.2015.02.048 Mathe, 2015, MiRNAs and other epigenetic changes as biomarkers in triple negative breast cancer, Int J Mol Sci, 16, 28347, 10.3390/ijms161226090 Bertoli, 2015, MicroRNAs: new biomarkers for diagnosis, prognosis, therapy prediction and therapeutic tools for breast cancer, Theranostics, 5, 1122, 10.7150/thno.11543 Avery-Kiejda, 2014, Decreased expression of key tumour suppressor microRNAs is associated with lymph node metastases in triple negative breast cancer, BMC Cancer, 14, 51, 10.1186/1471-2407-14-51 Koduru, 2017, A comprehensive NGS data analysis of differentially regulated miRNAs, piRNAs, lncRNAs and sn/snoRNAs in triple negative breast cancer, J Cancer, 8, 578, 10.7150/jca.17633 Garcia, 2011, Down-regulation of BRCA1 expression by miR-146a and miR-146b-5p in triple negative sporadic breast cancers, EMBO Mol Med, 3, 279, 10.1002/emmm.201100136 Taylor, 2013, TGF-β upregulates miR-181a expression to promote breast cancer metastasis, J Clin Invest, 123, 150, 10.1172/JCI64946 Bisso, 2013, Oncogenic miR-181a/b affect the DNA damage response in aggressive breast cancer, Cell Cycle, 12, 1679, 10.4161/cc.24757 Johansson, 2013, MiR-155-mediated loss of C/EBPβ shifts the TGF-β response from growth inhibition to epithelial-mesenchymal transition, invasion and metastasis in breast cancer, Oncogene, 32, 5614, 10.1038/onc.2013.322 Kong, 2014, Upregulation of miRNA-155 promotes tumour angiogenesis by targeting VHL and is associated with poor prognosis and triple-negative breast cancer, Oncogene, 33, 679, 10.1038/onc.2012.636 MacKenzie, 2014, Stromal expression of miR-21 identifies high-risk group in triple-negative breast cancer, Am J Pathol, 184, 3217, 10.1016/j.ajpath.2014.08.020 Fang, 2017, miRNA-21 promotes proliferation and invasion of triple-negative breast cancer cells through targeting PTEN, Am J Transl Res, 9, 953 Das, 2016, miR-720 is a downstream target of an ADAM8-induced ERK signaling cascade that promotes the migratory and invasive phenotype of triple-negative breast cancer cells, Breast Cancer Res, 18, 40, 10.1186/s13058-016-0699-z Li, 2017, MicroRNA-455-3p promotes invasion and migration in triple negative breast cancer by targeting tumor suppressor EI24, Oncotarget, 8, 19455, 10.18632/oncotarget.14307 Truong, 2014, β1 integrin inhibition elicits a prometastatic switch through the TGFβ-miR-200-ZEB network in E-cadherin-positive triple-negative breast cancer, Sci Signal, 7, ra15, 10.1126/scisignal.2004751 Tsouk, 2015, miR-200a inhibits migration of triple-negative breast cancer cells through direct repression of the EPHA2 oncogene, Carcinogenesis, 36, 1051, 10.1093/carcin/bgv087 D'Ippolito, 2016, miR-9 and miR-200 regulate PDGFRβ-mediated endothelial differentiation of tumor cells in triple-negative breast cancer, Cancer Res, 76, 5562, 10.1158/0008-5472.CAN-16-0140 Adams, 2016, miR-34a silences c-SRC to attenuate tumor growth in triple-negative breast cancer, Cancer Res, 76, 927, 10.1158/0008-5472.CAN-15-2321 Liu, 2016, microRNA-497 modulates breast cancer cell proliferation, invasion, and survival by targeting SMAD7, DNA Cell Biol, 35, 521, 10.1089/dna.2016.3282 Phan, 2016, Tumor suppressor role of microRNA-1296 in triple-negative breast cancer, Oncotarget, 7, 19519, 10.18632/oncotarget.6961 Sun, 2016, MicroRNA-223 increases the sensitivity of triple-negative breast cancer stem cells to trail-induced apoptosis by targeting HAX-1, PLoS One, 11, e0162754, 10.1371/journal.pone.0162754 Chen, 2017, MicroRNA-211-5p suppresses tumour cell proliferation, invasion, migration and metastasis in triple-negative breast cancer by directly targeting SETBP1, Br J Cancer, 117, 78, 10.1038/bjc.2017.150 Zhou, 2017, miR-217 inhibits triple-negative breast cancer cell growth, migration, and invasion through targeting KLF5, PLoS One, 12, e0176395, 10.1371/journal.pone.0176395 Kota, 2009, Therapeutic microRNA delivery suppresses tumorigenesis in a murine liver cancer model, Cell, 137, 1005, 10.1016/j.cell.2009.04.021 Ling, 2013, MicroRNAs and other non-coding RNAs as targets for anticancer drug development, Nat Rev Drug Discov, 12, 847, 10.1038/nrd4140 Li, 2014, Therapeutic targeting of microRNAs: current status and future challenges, Nat Rev Drug Discov, 13, 622, 10.1038/nrd4359 Cheng, 2015, MicroRNA silencing for cancer therapy targeted to the tumour microenvironment, Nature, 518, 107, 10.1038/nature13905 Shu, 2015, Systemic delivery of anti-miRNA for suppression of triple negative breast cancer utilizing RNA nanotechnology, ACS Nano, 9, 9731, 10.1021/acsnano.5b02471 Beavers, 2016, Porous silicon and polymer nanocomposites for delivery of peptide nucleic acids as anti-microRNA therapies, Adv Mater, 28, 7984, 10.1002/adma.201601646 Rupaimoole, 2017, MicroRNA therapeutics: towards a new era for the management of cancer and other diseases, Nat Rev Drug Discov, 16, 203, 10.1038/nrd.2016.246 Xie, 2013, A helm model for microRNA regulation in cell fate decision and conversion, Sci China Life Sci, 56, 897, 10.1007/s11427-013-4547-4 Fang, 2011, Breast cancer methylomes establish an epigenomic foundation for metastasis, Sci Transl Med, 3, 75ra25, 10.1126/scitranslmed.3001875 Stirzaker, 2015, Methylome sequencing in triple-negative breast cancer reveals distinct methylation clusters with prognostic value, Nat Commun, 6, 5899, 10.1038/ncomms6899 Jones, 2016, Targeting the cancer epigenome for therapy, Nat Rev Genet, 17, 630, 10.1038/nrg.2016.93 Zhao, 2016, Global histone modification profiling reveals the epigenomic dynamics during malignant transformation in a four-stage breast cancer model, Clin Epigenetics, 8, 34, 10.1186/s13148-016-0201-x Fleischer, 2017, DNA methylation at enhancers identifies distinct breast cancer lineages, Nat Commun, 8, 1379, 10.1038/s41467-017-00510-x Geiger, 2012, Proteomic portrait of human breast cancer progression identifies novel prognostic markers, Cancer Res, 72, 2428, 10.1158/0008-5472.CAN-11-3711 Muñiz Lino, 2014, Comparative proteomic profiling of triple-negative breast cancer reveals that up-regulation of RhoGDI-2 is associated to the inhibition of caspase 3 and caspase 9, J Proteomics, 111, 198, 10.1016/j.jprot.2014.04.019 Lawrence, 2015, The proteomic landscape of triple-negative breast cancer, Cell Rep, 11, 630, 10.1016/j.celrep.2015.03.050 Tyanova, 2016, Proteomic maps of breast cancer subtypes, Nat Commun, 7, 10259, 10.1038/ncomms10259 Huang, 2017, Protein array-based approaches for biomarker discovery in cancer, Genomics Proteomics Bioinformatics, 15, 73, 10.1016/j.gpb.2017.03.001 Li, 2017, Recent progress in mass spectrometry proteomics for biomedical research, Sci China Life Sci, 60, 1093, 10.1007/s11427-017-9175-2 Denkert, 2012, Metabolomics of human breast cancer: new approaches for tumor typing and biomarker discovery, Genome Med, 4, 37, 10.1186/gm336 Mishra, 2015, Metabolic signatures of human breast cancer, Mol Cell Oncol, 2, e992217, 10.4161/23723556.2014.992217 Huang, 2016, Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis, Genome Med, 8, 34, 10.1186/s13073-016-0289-9 Shen, 2013, Interplay between the cancer genome and epigenome, Cell, 153, 38, 10.1016/j.cell.2013.03.008 Clare, 2016, “Big Data” for breast cancer: where to look and what you will find, NPJ Breast Cancer, 2, 16031, 10.1038/npjbcancer.2016.31 Sandhu, 2018, Panomics for precision medicine, Trends Mol Med, 24, 85, 10.1016/j.molmed.2017.11.001 Letai, 2017, Functional precision cancer medicine—moving beyond pure genomics, Nat Med, 23, 1028, 10.1038/nm.4389 Wang, 2017, Disease biomarkers for precision medicine: challenges and future opportunities, Genomics Proteomics Bioinformatics, 15, 57, 10.1016/j.gpb.2017.04.001 Soysal, 2015, Role of the tumor microenvironment in breast cancer, Pathobiology, 82, 142, 10.1159/000430499 Weinberg, 2014, Coming full circle—from endless complexity to simplicity and back again, Cell, 157, 267, 10.1016/j.cell.2014.03.004 Alyass, 2015, From big data analysis to personalized medicine for all: challenges and opportunities, BMC Med Genomics, 8, 33, 10.1186/s12920-015-0108-y Elefsinioti, 2016, Key factors for successful data integration in biomarker research, Nat Rev Drug Discov, 15, 369, 10.1038/nrd.2016.74 McCue, 2017, The scope of big data in one medicine: unprecedented opportunities and challenges, Front Vet Sci, 4, 194, 10.3389/fvets.2017.00194 Huang, 2017, More is better: recent progress in multi-omics data integration methods, Front Genet, 8, 84, 10.3389/fgene.2017.00084