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OMICs Profiling of Cancer Cells

  • Bagher Larijani
  • Parisa Goodarzi
  • Motahareh Sheikh Hosseini
  • Solmaz M. Nejad
  • Sepideh Alavi-Moghadam
  • Masoumeh Sarvari
  • Mina Abedi
  • Maryam Arabi
  • Fakher Rahim
  • Najmeh Foroughi Heravani
  • Mahdieh Hadavandkhani
  • Moloud Payab
Chapter
Part of the Stem Cell Biology and Regenerative Medicine book series (STEMCELL)

Abstract

The number of people survive from cancer is increasing in the USA due to the advances in the early detection and treatment. Cancer is a complex disease caused by several factors such as genetics, epigenetics, proteomics, and transcriptional alterations or cellular damage that is resulted from several factors through genetic mutations and environmental effects. Early diagnosis has a pivotal role in the treatment or improving outcomes of cancer. Therefore, detecting cancer at early stages is a key challenge in cancer medicine and increases the survival rate. For early diagnosis, some genetics, proteomics, and metabolomics profiling should be considered using OMICs technologies. Traditional technologies using simplistic approach such as chemotherapy and surgery are relatively insufficient to facing challenges in the treatment of cancer. As a result, OMICs technologies mainly focus on the detection of entire genes which is applied into genomics, mRNA (transcriptomics), proteins (proteomics), metabolites (metabolomics), and lipids (lipidomics) in cells. The term genomics refers to the study of structure and function of DNA. Gene expression studies which is referred to transcriptomics are one of the oldest OMICs technologies, as it is the analysis of the entire RNA sequences in a cell. Proteomics technologies can identify the protein changes caused by disease process. Metabolomics is the study of small molecules, which are metabolites and are found in cells, tissues, and bio-fluids of an organism. Patterns of plasma lipid opulence are referred to as the lipidome. OMICs technologies, which system biology bring, are valuable tools for comprehensive analysis. The availability of DNA sequencing automatically enabled the sequencing of genomes; immunohistochemistry, which is one of the protein-based histopathological assays, has been the traditional basis of laboratory-based tumor characterization. Microarray and mass spectrometry analysis enabled comprehensive transcriptional profiling and lead to large-scale proteomics and metabolomics analysis. Scientists hope that with future analyzing of OMICs data, we can increase our therapeutic productivity for molecular targets of cancer therapies. The data of cancer OMICs are rapidly collected and provided an invaluable resource for identifying novel targets in the treatment of cancer, and will accelerate with developed diagnostic technologies and advanced novel methods in near future.

Keywords

Biomarkers Cancer Early detection OMICs technology Treatment associated 

Notes

Acknowledgement

The authors would like to acknowledge Maryam Afshari and Dr. Mohsen Khorshidi for their kind support.

References

  1. 1.
    Swann R, et al. Diagnosing cancer in primary care: results from the National Cancer Diagnosis Audit. Br J Gen Pract. 2018;68(666):e63–72.PubMedCrossRefGoogle Scholar
  2. 2.
    Siegel R, et al. Cancer statistics, 2019. CA Cancer J Clin. 2019;69(1):7–34.CrossRefGoogle Scholar
  3. 3.
    Miller K, et al. Cancer treatment and survivorship statistics. CA Cancer J Clin. 2016;66(4):271–89.PubMedCrossRefPubMedCentralGoogle Scholar
  4. 4.
    Karczewski K, Snyder M. Integrative omics for health and disease. Nat Rev Genet. 2018;19(5):229.CrossRefGoogle Scholar
  5. 5.
    Yoo B, et al. Clinical multi-omics strategies for the effective cancer management. J Proteome. 2018;30(188):97–106.CrossRefGoogle Scholar
  6. 6.
    Cho WC-S, editor. An omics perspective on cancer research. Dordrecht: Springer; 2010. p. 1–9.CrossRefGoogle Scholar
  7. 7.
    Rapisuwon S, Vietsch E, Wellstein A. Circulating biomarkers to monitor cancer progression and treatment. Comput Struct Biotechnol J. 2016;1(14):211–22.CrossRefGoogle Scholar
  8. 8.
    Yu K, Snyder M. Omics profiling in precision oncology. Mol Cell Proteomics. 2016;15(8):2525–36.PubMedPubMedCentralCrossRefGoogle Scholar
  9. 9.
    Holzinger A, Dehmer M, Murisica I. Knowledge discovery and interactive data mining in bioinformatics-state-of-the-art, future challenges and research directions. BMC Bioinformatics. 2014;15(6):1.CrossRefGoogle Scholar
  10. 10.
    Moreno-Sánchez R, et al. Understanding the cancer cell phenotype beyond the limitations of current omics analyses. FEBS J. 2016;283(1):54–73.PubMedCrossRefPubMedCentralGoogle Scholar
  11. 11.
    Zhang X, et al. Mass spectrometry-based “omics” technologies in cancer diagnostics. Mass Spectrom Rev. 2007;26(3):403–31.PubMedCrossRefPubMedCentralGoogle Scholar
  12. 12.
    Radpour R, Forouharkhou F. Single-cell analysis of tumors: creating new value for molecular biomarker discovery of cancer stem cells and tumor-infiltrating immune cells. World J Stem Cells. 2018;10(11):160.PubMedPubMedCentralCrossRefGoogle Scholar
  13. 13.
    Carlomagno N, et al. Diagnostic, predictive, prognostic, and therapeutic molecular biomarkers in third millennium: a breakthrough in gastric cancer. Biomed Res Int. 2017;2017:7869802.PubMedPubMedCentralCrossRefGoogle Scholar
  14. 14.
    Wang D, Bodovitz S. Single cell analysis: the new frontier in ‘omics’. Trends Biotechnol. 2010;28(6):281–90.PubMedPubMedCentralCrossRefGoogle Scholar
  15. 15.
    Milestones in cancer research and discovery. 2015 Jan 21. https://www.cancer.gov/research/progress/250-years-milestones.
  16. 16.
    Saijo N, et al. New strategies for cancer therapy in the 21st century. Cancer Chemother Pharmacol. 2001;48(1):102–6.CrossRefGoogle Scholar
  17. 17.
    Kangwan N, et al. Chemoquiescence for ideal cancer treatment and prevention: where are we now? J Cancer Prev. 2014;19(2):89–96.PubMedPubMedCentralCrossRefGoogle Scholar
  18. 18.
    Charmsaz S, et al. Innovative technologies changing cancer treatment. Cancers (Basel). 2018;10(6):208.CrossRefGoogle Scholar
  19. 19.
    The American Cancer Society Medical and Editorial Content Team. The history of cancer; evolution of cancer treatments: surgery. 2014 June 12. https://www.cancer.org/cancer/cancer-basics/history-of-cancer/cancer-treatment-surgery.html.
  20. 20.
    Stanford Health Care. Types of surgery for cancer treatment. https://stanfordhealthcare.org/medical-treatments/c/cancer-surgery/types.html.
  21. 21.
    Subotic S, Wyler S, Bachmann A. Surgical treatment of localised renal cancer. Eur Urol Suppl. 2012;11(3):60–5.CrossRefGoogle Scholar
  22. 22.
    Baskar R, et al. Cancer and radiation therapy: current advances and future directions. Int J Med Sci. 2012;9(3):193–9.PubMedPubMedCentralCrossRefGoogle Scholar
  23. 23.
    Chiang T, et al. Complete remission in very advanced oral cancer by docetaxel, cisplatin, 5-fluorouracil based induction chemotherapy followed by concurrent chemoradiation. J Dent Sci. 2018;13(1):82–4.PubMedCrossRefPubMedCentralGoogle Scholar
  24. 24.
    Yang Y. Cancer immunotherapy: harnessing the immune system to battle cancer. J Clin Invest. 2015;125(9):3335–7.PubMedPubMedCentralCrossRefGoogle Scholar
  25. 25.
    Armitage EG, Southam AD. Monitoring cancer prognosis, diagnosis and treatment efficacy using metabolomics and lipidomics. Metabolomics. 2016;12(9):146.PubMedPubMedCentralCrossRefGoogle Scholar
  26. 26.
    Triulzi T, Bianchi GV, Tagliabue E. Predictive biomarkers in the treatment of HER2-positive breast cancer: an ongoing challenge. Future Oncol. 2016;12(11):1413–28.PubMedCrossRefPubMedCentralGoogle Scholar
  27. 27.
    Wang Y, et al. UGT1A1 predicts outcome in colorectal cancer treated with irinotecan and fluorouracil. World J Gastroenterol. 2012;18(45):6635–44.PubMedPubMedCentralCrossRefGoogle Scholar
  28. 28.
    Abrahao-Machado LF, Scapulatempo-Neto C. HER2 testing in gastric cancer: an update. World J Gastroenterol. 2016;22(19):4619–25.PubMedPubMedCentralCrossRefGoogle Scholar
  29. 29.
    Prevodnik VK, et al. The predictive significance of CD20 expression in B-cell lymphomas. Diagn Pathol. 2011;6:33.PubMedPubMedCentralCrossRefGoogle Scholar
  30. 30.
    Zheng W, et al. CD30 expression in high-risk acute myeloid leukemia and myelodysplastic syndromes. Clin Lymphoma Myeloma Leuk. 2013;13(3):307–14.PubMedPubMedCentralCrossRefGoogle Scholar
  31. 31.
    Minamimoto R, et al. Prediction of EGFR and KRAS mutation in non-small cell lung cancer using quantitative 18F FDG-PET/CT metrics. Oncotarget. 2017;8(32):52792–801.PubMedPubMedCentralCrossRefGoogle Scholar
  32. 32.
    Bhatia P, et al. Impact of BRAF mutation status in the prognosis of cutaneous melanoma: an area of ongoing research. Ann Transl Med. 2015;3(2):24.PubMedPubMedCentralGoogle Scholar
  33. 33.
    Wu L, Qu X. Cancer biomarker detection: recent achievements and challenges. Chem Soc Rev. 2015;44(10):2963–97.PubMedCrossRefGoogle Scholar
  34. 34.
    Sani M-RM, et al. Biomarkers in cancer. Immunopharmacogenetics. 2018;1:01.Google Scholar
  35. 35.
    Ludwig J, Weinstein J. Biomarkers in cancer staging, prognosis and treatment selection. Nat Rev Cancer. 2005;5(11):845.PubMedCrossRefGoogle Scholar
  36. 36.
    Wills Q, Mead AJ. Application of single-cell genomics in cancer: promise and challenges. Hum Mol Genet. 2015;24(R1):R74–84.PubMedPubMedCentralCrossRefGoogle Scholar
  37. 37.
    Romanov V, et al. A critical comparison of protein microarray fabrication technologies. Analyst. 2014;139(6):1303–26.PubMedCrossRefGoogle Scholar
  38. 38.
    Barbulovic-Nad I, et al. Bio-microarray fabrication techniques--a review. Crit Rev Biotechnol. 2006;26(4):237–59.PubMedCrossRefGoogle Scholar
  39. 39.
    Russell S, Meadows L, Russell R. Microarray technology in practice. Cambridge: Academic; 2008.Google Scholar
  40. 40.
    Wang Z, Gerstein M, syder M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet. 2009;10(1):57.PubMedPubMedCentralCrossRefGoogle Scholar
  41. 41.
    Srinivas P, et al. Proteomics for cancer biomarker discovery. Clin Chem. 2002;48(8):1160–9.PubMedPubMedCentralGoogle Scholar
  42. 42.
    Ostroff RM, et al. Unlocking biomarker discovery: large scale application of aptamer proteomic technology for early detection of lung cancer. PLoS One. 2010;5(12):e15003.PubMedPubMedCentralCrossRefGoogle Scholar
  43. 43.
    Auburn RP, et al. Robotic spotting of cDNA and oligonucleotide microarrays. Trends Biotechnol. 2005;23(7):374–9.PubMedCrossRefPubMedCentralGoogle Scholar
  44. 44.
    Mehrparavar B, et al. Metabolomics of male infertility: a new tool for diagnostic tests. J Reprod Infertil. 2019;20(2):64–9.PubMedPubMedCentralGoogle Scholar
  45. 45.
    Agharezaee N, et al. Metabolomics: a bird’s eye view of infertile men. Tehran Univ Med J TUMS Publ. 2018;75(12):860–8.Google Scholar
  46. 46.
    Khatami F, et al. Oncometabolites as biomarkers in thyroid cancer: a systematic review. Cancer Manag Res. 2019;11:1829.PubMedPubMedCentralCrossRefGoogle Scholar
  47. 47.
    Hammoudi N, et al. Metabolic alterations in cancer cells and therapeutic implications. Chin J Cancer. 2011;30(8):508.PubMedPubMedCentralCrossRefGoogle Scholar
  48. 48.
    Wishart D, et al. Cancer metabolomics and the human metabolome database. Meta. 2016;6(1):10.Google Scholar
  49. 49.
    Vucic EA, et al. Translating cancer ‘omics’ to improved outcomes. Genome Res. 2012;22(2):188–95.PubMedPubMedCentralCrossRefGoogle Scholar
  50. 50.
    Yoo BC, et al. Clinical multi-omics strategies for the effective cancer management. J Proteome. 2018;188:97–106.CrossRefGoogle Scholar
  51. 51.
    Epstein RJ, Lin F. Cancer and the omics revolution. Aust Fam Physician. 2017;46(4):189–93.PubMedPubMedCentralGoogle Scholar
  52. 52.
    Sokolenko AP, Imyanitov EN. Molecular diagnostics in clinical oncology. Front Mol Biosci. 2018;5:76.PubMedPubMedCentralCrossRefGoogle Scholar
  53. 53.
    Kubicek-Sutherland JZ, et al. Detection of lipid and Amphiphilic biomarkers for disease diagnostics. Biosensors (Basel). 2017;7(3):25.CrossRefGoogle Scholar
  54. 54.
    Karczewski KJ, Snyder MP. Integrative omics for health and disease. Nat Rev Genet. 2018;19(5):299.PubMedPubMedCentralCrossRefGoogle Scholar
  55. 55.
    M Toloudi PA, Chatziioannou M, Kourtidou E, Vlachou I, Mimikakou G, Chlichlia A, Papasotiriou I. Recent developments in cancer treatment: a review. Pharmaceut Reg Aff. 2014;S1:001.Google Scholar
  56. 56.
    Ramaswami R, Harding V, Newsom-Davis T. Novel cancer therapies: treatments driven by tumour biology. Postgrad Med J. 2013;89:652–8.PubMedCrossRefPubMedCentralGoogle Scholar
  57. 57.
    Chakraborty C, et al. The novel strategies for next-generation cancer treatment: miRNA combined with chemotherapeutic agents for the treatment of cancer. Oncotarget. 2018;9(11):10164–74.PubMedPubMedCentralCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Bagher Larijani
    • 1
  • Parisa Goodarzi
    • 2
  • Motahareh Sheikh Hosseini
    • 3
  • Solmaz M. Nejad
    • 4
  • Sepideh Alavi-Moghadam
    • 4
  • Masoumeh Sarvari
    • 3
  • Mina Abedi
    • 4
  • Maryam Arabi
    • 4
  • Fakher Rahim
    • 5
  • Najmeh Foroughi Heravani
    • 4
  • Mahdieh Hadavandkhani
    • 4
  • Moloud Payab
    • 6
  1. 1.Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences InstituteTehran University of Medical SciencesTehranIran
  2. 2.Brain and Spinal Cord Injury Research Center, Neuroscience InstituteTehran University of Medical SciencesTehranIran
  3. 3.Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences InstituteTehran University of Medical SciencesTehranIran
  4. 4.Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences InstituteTehran University of Medical SciencesTehranIran
  5. 5.Health Research Institute, Thalassemia and Hemoglobinopathies Research CenterAhvaz Jundishapur University of Medical SciencesAhvazIran
  6. 6.Obesity and Eating Habits Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences InstituteTehran University of Medical SciencesTehranIran

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