The Need for Multi-Omics Biomarker Signatures in Precision Medicine

Recent advances in omics technologies have led to unprecedented efforts characterizing the molecular changes that underlie the development and progression of a wide array of complex human diseases, including cancer. As a result, multi-omics analyses—which take advantage of these technologies in genomics, transcriptomics, epigenomics, proteomics, metabolomics, and other omics areas—have been proposed and heralded as the key to advancing precision medicine in the clinic. In the field of precision oncology, genomics approaches, and, more recently, other omics analyses have helped reveal several key mechanisms in cancer development, treatment resistance, and recurrence risk, and several of these findings have been implemented in clinical oncology to help guide treatment decisions. However, truly integrated multi-omics analyses have not been applied widely, preventing further advances in precision medicine. Additional efforts are needed to develop the analytical infrastructure necessary to generate, analyze, and annotate multi-omics data effectively to inform precision medicine-based decision-making.

[1]  Wei Jia,et al.  Novel Applications of Metabolomics in Personalized Medicine: A Mini-Review , 2017, Molecules.

[2]  Frank Stahl,et al.  Transcriptome analysis using next-generation sequencing. , 2013, Current opinion in biotechnology.

[3]  Eddy J. Bautista,et al.  Integrative Personal Omics Profiles during Periods of Weight Gain and Loss. , 2018, Cell systems.

[4]  Martin E. Fernandez-Zapico,et al.  Faculty Opinions recommendation of Elevation of circulating branched-chain amino acids is an early event in human pancreatic adenocarcinoma development. , 2015 .

[5]  Z. Kokot,et al.  Understanding Ovarian Cancer: iTRAQ-Based Proteomics for Biomarker Discovery , 2018, International journal of molecular sciences.

[6]  David T. W. Jones,et al.  Signatures of mutational processes in human cancer , 2013, Nature.

[7]  A. Kurian BRCA1 and BRCA2 mutations across race and ethnicity: distribution and clinical implications , 2010, Current opinion in obstetrics & gynecology.

[8]  Olaf Sporns,et al.  The Human Connectome: A Structural Description of the Human Brain , 2005, PLoS Comput. Biol..

[9]  Thumuluru Kavitha Madhuri,et al.  Proteomics Analysis of Ovarian Cancer Cell Lines and Tissues Reveals Drug Resistance-associated Proteins. , 2017, Cancer genomics & proteomics.

[10]  Gord Glendon,et al.  Association Between BRCA1 and BRCA2 Mutations and Survival in Women With Invasive Epithelial Ovarian Cancer , 2012 .

[11]  James E Audia,et al.  Histone Modifications and Cancer. , 2016, Cold Spring Harbor perspectives in biology.

[12]  Ryan A Kellogg,et al.  Personal Omics for Precision Health , 2018, Circulation research.

[13]  Krister Wennerberg,et al.  Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approach , 2017, Bioinform..

[14]  Satya P Yadav,et al.  The wholeness in suffix -omics, -omes, and the word om. , 2007, Journal of biomolecular techniques : JBT.

[15]  E. Winzeler,et al.  Protein pathway and complex clustering of correlated mRNA and protein expression analyses in Saccharomyces cerevisiae , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[16]  Itay Tirosh,et al.  Single-Cell RNA Sequencing in Cancer: Lessons Learned and Emerging Challenges. , 2019, Molecular cell.

[17]  G. Weinstock,et al.  A Longitudinal Big Data Approach for Precision Health , 2019, Nature Medicine.

[18]  J. Handelsman,et al.  Metagenomics: genomic analysis of microbial communities. , 2004, Annual review of genetics.

[19]  Howard Y. Chang,et al.  Epigenomics: Technologies and Applications , 2018, Circulation research.

[20]  Lovelace J. Luquette,et al.  Landscape of Somatic Retrotransposition in Human Cancers , 2012, Science.

[21]  S. Gabriel,et al.  Activating mTOR mutations in a patient with an extraordinary response on a phase I trial of everolimus and pazopanib. , 2014, Cancer discovery.

[22]  Li Ding,et al.  Driver Fusions and Their Implications in the Development and Treatment of Human Cancers , 2018, Cell reports.

[23]  R. Shamir,et al.  Multi-omic and multi-view clustering algorithms: review and cancer benchmark , 2018, bioRxiv.

[24]  Biswapriya B Misra,et al.  Integrated Omics: Tools, Advances, and Future Approaches. , 2019, Journal of molecular endocrinology.

[25]  Giuseppe Maruccio,et al.  Cell chips as new tools for cell biology--results, perspectives and opportunities. , 2013, Lab on a chip.

[26]  L. Qiu,et al.  Serum Unsaturated Free Fatty Acids: A Potential Biomarker Panel for Early-Stage Detection of Colorectal Cancer , 2016, Journal of Cancer.

[27]  Xianlin Han,et al.  Shotgun lipidomics: multidimensional MS analysis of cellular lipidomes , 2005, Expert review of proteomics.

[28]  Stacy D. Sherrod,et al.  Untargeted Metabolomics Strategies—Challenges and Emerging Directions , 2016, Journal of The American Society for Mass Spectrometry.

[29]  S. Beck,et al.  From profiles to function in epigenomics , 2016, Nature Reviews Genetics.

[30]  Tamar Geiger,et al.  Clinical Proteomics of Breast Cancer Reveals a Novel Layer of Breast Cancer Classification. , 2018, Cancer research.

[31]  Zhirong Sun,et al.  High Accordance in Prognosis Prediction of Colorectal Cancer across Independent Datasets by Multi-Gene Module Expression Profiles , 2012, PloS one.

[32]  Yan V. Sun,et al.  Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases. , 2016, Advances in genetics.

[33]  S. Elledge,et al.  Tumor aneuploidy correlates with markers of immune evasion and with reduced response to immunotherapy , 2017, Science.

[34]  R. Mirimanoff,et al.  MGMT gene silencing and benefit from temozolomide in glioblastoma. , 2005, The New England journal of medicine.

[35]  David Killock CNS cancer: Molecular classification of glioma , 2015, Nature Reviews Clinical Oncology.

[36]  K. Tomczak,et al.  The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge , 2015, Contemporary oncology.

[37]  Mats Lambe,et al.  Biomarker Discovery in Non–Small Cell Lung Cancer: Integrating Gene Expression Profiling, Meta-analysis, and Tissue Microarray Validation , 2012, Clinical Cancer Research.

[38]  R. Houlston,et al.  Genome-wide association studies of cancer: current insights and future perspectives , 2017, Nature Reviews Cancer.

[39]  Victor X. Jin,et al.  Single-Cell RNA-seq Reveals a Subpopulation of Prostate Cancer Cells with Enhanced Cell-Cycle-Related Transcription and Attenuated Androgen Response. , 2018, Cancer research.

[40]  D. Carraro,et al.  Mismatch repair genes in Lynch syndrome: a review , 2009, Sao Paulo medical journal = Revista paulista de medicina.

[41]  A. McKenna,et al.  Integrative eQTL-Based Analyses Reveal the Biology of Breast Cancer Risk Loci , 2013, Cell.

[42]  Jeffrey W. Clark,et al.  A protein and mRNA expression-based classification of gastric cancer , 2016, Modern Pathology.

[43]  Kubra Karagoz,et al.  A Network-Based Cancer Drug Discovery: From Integrated Multi-Omics Approaches to Precision Medicine. , 2019, Current pharmaceutical design.

[44]  Saumyadipta Pyne,et al.  A brief review of single-cell transcriptomic technologies. , 2018, Briefings in functional genomics.

[45]  A. Lusis,et al.  Considerations for the design of omics studies , 2017 .

[46]  Winston Haynes,et al.  Integrative Analysis of Longitudinal Metabolomics Data from a Personal Multi-Omics Profile , 2013, Metabolites.

[47]  Joshua M. Stuart,et al.  The Cancer Genome Atlas Pan-Cancer analysis project , 2013, Nature Genetics.

[48]  M. Wenk The emerging field of lipidomics , 2005, Nature Reviews Drug Discovery.

[49]  A. Bhan,et al.  Long Noncoding RNA and Cancer: A New Paradigm. , 2017, Cancer research.

[50]  E. Saleh,et al.  Epigenetics and miRNA as predictive markers and targets for lung cancer chemotherapy , 2015, Cancer biology & therapy.

[51]  Steven J. M. Jones,et al.  Comprehensive, Integrative Genomic Analysis of Diffuse Lower-Grade Gliomas. , 2015, The New England journal of medicine.

[52]  Li Yu,et al.  [DNA methylation and cancer]. , 2005, Zhonghua nei ke za zhi.

[53]  M. Khurshid,et al.  Proteomics: Technologies and Their Applications. , 2017, Journal of chromatographic science.

[54]  Charles H. Yoon,et al.  Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq , 2016, Science.

[55]  Xiaoping Zhou,et al.  Whole transcriptome analysis with sequencing: methods, challenges and potential solutions , 2015, Cellular and Molecular Life Sciences.

[56]  Wei Zhang,et al.  Dissecting intratumoral myeloid cell plasticity by single cell RNA‐seq , 2019, Cancer medicine.

[57]  Thomas J. Wang,et al.  Branched-Chain Amino Acids and Cardiovascular Disease: Does Diet Matter? , 2016, Clinical chemistry.

[58]  G. Daley,et al.  The chronic myelogenous leukemia-specific P210 protein is the product of the bcr/abl hybrid gene. , 1986, Science.

[59]  Y. Mo,et al.  LncRNA-mediated regulation of cell signaling in cancer , 2017, Oncogene.

[60]  G. Gibson On the utilization of polygenic risk scores for therapeutic targeting , 2019, PLoS genetics.

[61]  Steve Horvath,et al.  WGCNA: an R package for weighted correlation network analysis , 2008, BMC Bioinformatics.

[62]  J. Paulson,et al.  Glycomics: an integrated systems approach to structure-function relationships of glycans , 2005, Nature Methods.

[63]  T. Bathen,et al.  Spermine and Citrate as Metabolic Biomarkers for Assessing Prostate Cancer Aggressiveness , 2013, PloS one.

[64]  Li Ding,et al.  Comprehensive Characterization of Cancer Driver Genes and Mutations (vol 173, 371.e1, 2018) , 2018 .

[65]  M. Ocker,et al.  Epigenetics and pancreatic cancer: pathophysiology and novel treatment aspects. , 2014, World journal of gastroenterology.

[66]  Andrew H. Beck,et al.  A diverse array of cancer-associated MTOR mutations are hyperactivating and can predict rapamycin sensitivity. , 2014, Cancer discovery.

[67]  E. Chiocca,et al.  Therapeutic potential of targeting microRNA‐10b in established intracranial glioblastoma: first steps toward the clinic , 2016, EMBO molecular medicine.

[68]  David Malkin,et al.  Inherited TP53 Mutations and the Li-Fraumeni Syndrome. , 2017, Cold Spring Harbor perspectives in medicine.

[69]  E. Lengyel,et al.  MicroRNAs as mediators and communicators between cancer cells and the tumor microenvironment , 2015, Oncogene.

[70]  X. Cui,et al.  Expression Signature of IFN/STAT1 Signaling Genes Predicts Poor Survival Outcome in Glioblastoma Multiforme in a Subtype-Specific Manner , 2012, PloS one.

[71]  Rong Yin,et al.  Forward and reverse mutations in stages of cancer development , 2018, Human Genomics.

[72]  A. Cifuentes Food analysis and foodomics. , 2009, Journal of chromatography. A.

[73]  J. Witte,et al.  Cis-eQTL-based trans-ethnic meta-analysis reveals novel genes associated with breast cancer risk , 2017, PLoS genetics.

[74]  Steven Gallinger,et al.  Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations. , 2016, Cancer research.

[75]  Ruedi Aebersold,et al.  Mass-spectrometric exploration of proteome structure and function , 2016, Nature.

[76]  Ulrich Lehmann,et al.  Mutant IDH1 promotes leukemogenesis in vivo and can be specifically targeted in human AML. , 2013, Blood.

[77]  S. Gabriel,et al.  Pan-cancer patterns of somatic copy-number alteration , 2013, Nature Genetics.

[78]  Pietro Hiram Guzzi,et al.  From Single Level Analysis to Multi-Omics Integrative Approaches: A Powerful Strategy towards the Precision Oncology , 2018, High-throughput.

[79]  H. Daniel,et al.  Branched-chain amino acids as biomarkers in diabetes. , 2016, Current opinion in clinical nutrition and metabolic care.

[80]  Jeong Eon Lee,et al.  Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer , 2017, Nature Communications.

[81]  Lawrence D. True,et al.  Integrative Clinical Genomics of Advanced Prostate Cancer , 2015, Cell.

[82]  Charles M. Perou,et al.  Practical implications of gene-expression-based assays for breast oncologists , 2012, Nature Reviews Clinical Oncology.

[83]  D. Braconi,et al.  Foodomics for human health: current status and perspectives , 2018, Expert review of proteomics.

[84]  N. McGranahan,et al.  The causes and consequences of genetic heterogeneity in cancer evolution , 2013, Nature.