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Applications of single-cell sequencing for human lung cancer: the progress and the future perspective

1 Department of Thorax Medicine, the First Affiliated Hospital of Shenzhen University, Shenzhen, PR China
2 Department of Thorax Medicine, Lunggang People’s Hospital, Shenzhen, PR China
3 Functional Genomics Group, National Heart and Lung Institute, Imperial College London, the United Kingdom

Special Issues: Single Cell analysis

Human lung cancer is an extremely heterogeneous disease. Cell heterogeneity and diversity are responsible for lung cancer’s invasion, metastasis and the resistance to therapies. Recent developments of single-cell analysis make it possible for DNA sequencing, RNA sequencing and genomic element sequencing for single-cells from lung cancer. Methodology of single-cell sequencing was improved to reduce the errors in the processes due to applying tiny amount of the genetic materials. The single-cell sequencing for lung cancer has begun to reveal the deep insights of the cancer evolution and provided the new targets for clinical care. In this review, we briefly describe the methods of isolation, amplification and sequencing of single-cells. We also discuss the current progress in the research of lung cancer and the future prospects in single-cell analysis for the disease.
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Keywords single-cell sequencing; lung cancer; circulating tumour cells; whole genome amplification; whole transcriptome amplification

Citation: Min Zhang, Shijun Lin, Wendi Xiao, Danhua Chen, Dongxia Yang, Youming Zhang. Applications of single-cell sequencing for human lung cancer: the progress and the future perspective. AIMS Biophysics, 2017, 4(2): 210-221. doi: 10.3934/biophy.2017.2.210


  • 1. Siegel RL, Miller KD, Jemal A (2015) Cancer statistics, 2015. CA Cancer J Clin 65: 5–29.    
  • 2. Herbst RS, Heymach JV, Lippman SM (2008) Lung cancer. N Engl J Med 359: 1367–1380.    
  • 3. Wang Y, Navin NE (2015) Advances and applications of single-cell sequencing technologies. Mol Cell 58: 598–609.    
  • 4. Navin NE (2015) The first five years of single-cell cancer genomics and beyond. Genome Res 25: 1499–1507.    
  • 5. Mroz EA, Tward AD, Pickering CR, et al. (2013) High intratumor genetic heterogeneity is related to worse outcome in patients with head and neck squamous cell carcinoma. Cancer 119: 3034–3042.    
  • 6. Xu X, Hou Y, Yin X, et al. (2012) Single-cell exome sequencing reveals single-nucleotide mutation characteristics of a kidney tumor. Cell 148: 886–895.    
  • 7. Gawad C, Koh W, Quake SR (2016) Single-cell genome sequencing: current state of the science. Nat Rev Genet 17: 175–188.    
  • 8. Kreso A, O'Brien CA, van Galen P, et al. (2013) Variable clonal repopulation dynamics influence chemotherapy response in colorectal cancer. Science 339: 543–548.    
  • 9. Ding L, Ellis MJ, Li S, et al. (2010) Genome remodelling in a basal-like breast cancer metastasis and xenograft. Nature 464: 999–1005.    
  • 10. Emmert-Buck MR, Bonner RF, Smith PD, et al. (1996) Laser capture microdissection. Science 274: 998–1001.    
  • 11. Altomare L, Borgatti M, Medoro G, et al. (2003) Levitation and movement of human tumor cells using a printed circuit board device based on software-controlled dielectrophoresis. Biotechnol Bioeng 82: 474–479.    
  • 12. Choi JH, Ogunniyi AO, Du M, et al. (2010) Development and optimization of a process for automated recovery of single cells identified by microengraving. Biotechnol Prog 26: 888–895.    
  • 13. Adams DL, Martin SS, Alpaugh RK, et al. (2014) Circulating giant macrophages as a potential biomarker of solid tumors. Proc Natl Acad Sci USA 111: 3514–3519.    
  • 14. Leung ML, Wang Y, Waters J, et al. (2015) SNES: single nucleus exome sequencing. Genome Biol 16: 55.    
  • 15. Livesey FJ (2003) Strategies for microarray analysis of limiting amounts of RNA. Brief Funct Genomic Proteomic 2: 31–36.    
  • 16. Zhang CZ, Adalsteinsson VA, Francis J, et al. (2015) Calibrating genomic and allelic coverage bias in single-cell sequencing. Nat Commun 6: 6822.
  • 17. Navin N, Kendall J, Troge J, et al. (2011) Tumour evolution inferred by single-cell sequencing. Nature 472: 90–94.    
  • 18. Baslan T, Kendall J, Rodgers L, et al. (2012) Genome-wide copy number analysis of single cells. Nat Protoc 7: 1024–1041.    
  • 19. Hou Y, Song L, Zhu P, et al. (2012) Single-cell exome sequencing and monoclonal evolution of a JAK2-negative myeloproliferative neoplasm. Cell 148: 873–885.
  • 20. Zong C, Lu S, Chapman AR, et al. (2012) Genome-wide detection of single-nucleotide and copy-number variations of a single human cell. Science 338: 1622–1626.    
  • 21. Wang Y, Waters J, Leung ML, et al. (2014) Clonal evolution in breast cancer revealed by single nucleus genome sequencing. Nature 512: 155–160.    
  • 22. Zhang C, Zhang C, Chen S, et al. (2013) A single cell level based method for copy number variation analysis by low coverage massively parallel sequencing. PLoS One 8: e54236.    
  • 23. Zhang C, Cai H, Huang J, et al. (2016) nbCNV: a multi-constrained optimization model for discovering copy number variants in single-cell sequencing data. BMC Bioinformatics 17: 384.    
  • 24. Marinov GK, Williams BA, McCue K, et al. (2014) From single-cell to cell-pool transcriptomes: stochasticity in gene expression and RNA splicing. Genome Res 24: 496–510.
  • 25. Zhang X, Marjani SL, Hu Z, et al. (2016) Single-cell sequencing for precise cancer research: progress and prospects. Cancer Res 76: 1305–1312.    
  • 26. Kim KT, Lee HW, Lee HO, et al. (2015) Single-cell mRNA sequencing identifies subclonal heterogeneity in anti-cancer drug responses of lung adenocarcinoma cells. Genome Biol 16: 127.
  • 27. Saliba AE, Westermann AJ, Gorski SA, et al. (2014) Single-cell RNA-seq: advances and future challenges. Nucleic Acids Res 42: 8845–8860.    
  • 28. Tang F, Barbacioru C, Wang Y, et al. (2009) mRNA-Seq whole-transcriptome analysis of a single cell. Nat Methods 6: 377–382.    
  • 29. Ramskold D, Luo S, Wang YC, et al. (2012) Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells. Nat Biotechnol 30: 777–782.    
  • 30. Islam S, Zeisel A, Joost S, et al. (2014) Quantitative single-cell RNA-seq with unique molecular identifiers. Nat Methods 11: 163–166.
  • 31. Pollen AA, Nowakowski TJ, Shuga J, et al. (2014) Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex. Nat Biotechnol 32: 1053–1058.    
  • 32. Eirew P, Steif A, Khattra J, et al. (2015) Dynamics of genomic clones in breast cancer patient xenografts at single-cell resolution. Nature 518: 422–426.
  • 33. Stegle O, Teichmann SA, Marioni JC (2015) Computational and analytical challenges in single-cell transcriptomics. Nat Rev Genet 16: 133–145.
  • 34. Picelli S, Faridani OR, Bjorklund AK, et al. (2014) Full-length RNA-seq from single cells using Smart-seq2. Nat Protoc 9: 171–181.    
  • 35. Hashimshony T, Wagner F, Sher N, et al. (2012) CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification. Cell Rep 2: 666–673.    
  • 36. Jaitin DA, Kenigsberg E, Keren-Shaul H, et al. (2014) Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science 343: 776–779.    
  • 37. Islam S, Kjallquist U, Moliner A, et al. (2012) Highly multiplexed and strand-specific single-cell RNA 5' end sequencing. Nat Protoc 7: 813–828.    
  • 38. Macaulay IC, Haerty W, Kumar P, et al. (2015) G&T-seq: parallel sequencing of single-cell genomes and transcriptomes. Nat Methods 12: 519–522.    
  • 39. Dey SS, Kester L, Spanjaard B, et al. (2015) Integrated genome and transcriptome sequencing of the same cell. Nat Biotechnol 33: 285–289.
  • 40. Jin W, Tang Q, Wan M, et al. (2015) Genome-wide detection of DNase I hypersensitive sites in single cells and FFPE tissue samples. Nature 528: 142–146.
  • 41. Ziller MJ, Gu H, Muller F, et al. (2015) Charting a dynamic DNA methylation landscape of the human genome. Nature 500: 477–481.
  • 42. Hovestadt V, Jones DT, Picelli S, et al. (2014) Decoding the regulatory landscape of medulloblastoma using DNA methylation sequencing. Nature 510: 537–541.    
  • 43. Guo H, Zhu P, Guo F, et al. (2015) Profiling DNA methylome landscapes of mammalian cells with single-cell reduced-representation bisulfite sequencing. Nat Protoc 10: 645–659.
  • 44. Smallwood SA, Lee HJ, Angermueller C, et al. (2014) Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity. Nat Methods 11: 817–820.    
  • 45. Suzuki A, Matsushima K, Makinoshima H, et al. (2015) Single-cell analysis of lung adenocarcinoma cell lines reveals diverse expression patterns of individual cells invoked by a molecular target drug treatment. Genome Biol 16: 66.
  • 46. Cancer Genome Atlas Research Network (2014) Comprehensive molecular profiling of lung adenocarcinoma. Nature 511: 543–550.
  • 47. Willers H, Azzoli CG, Santivasi WL, et al. (2013) Basic mechanisms of therapeutic resistance to radiation and chemotherapy in lung cancer. Cancer J 19: 200–207.    
  • 48. Navin N, Krasnitz A, Rodgers L, et al. (2010) Inferring tumor progression from genomic heterogeneity. Genome Res 20: 68–80.
  • 49. Dawson SJ, Tsui DW, Murtaza M, et al. (2013) Analysis of circulating tumor DNA to monitor metastatic breast cancer. N Engl J Med 368: 1199–1209.    
  • 50. Jamal-Hanjani M, Hackshaw A, Ngai Y, et al. (2014) Tracking genomic cancer evolution for precision medicine: the lung TRACERx study. PLoS Biol 12: e1001906.    
  • 51. Min JW, Kim WJ, Han JA, et al. (2015) Identification of distinct tumor subpopulations in lung adenocarcinoma via single-cell RNA-seq. PLoS One 10: e0135817.    
  • 52. Heitzer E, Auer M, Ulz P, et al. (2013) Circulating tumor cells and DNA as liquid biopsies. Genome Med 5: 73.    
  • 53. Morimoto A, Mogami T, Watanabe M, et al. (2015) High-density dielectrophoretic microwell array for detection, capture, and single-cell analysis of rare tumor cells in peripheral blood. PLoS One 10: e0130418.
  • 54. Ni X, Zhuo M, Su Z, et al. (2013) Reproducible copy number variation patterns among single circulating tumor cells of lung cancer patients. Proc Natl Acad Sci USA 110: 21083–21088.    
  • 55. Ran R, Li L, Wang M, et al. (2013) Determination of EGFR mutations in single cells microdissected from enriched lung tumor cells in peripheral blood. Anal Bioanal Chem 405: 7377–7382.
  • 56. Carter L, Rothwell DG, Mesquita B, et al. (2017) Molecular analysis of circulating tumor cells identifies distinct copy-number profiles in patients with chemosensitive and chemorefractory small-cell lung cancer. Nat Med 23: 114–119.
  • 57. Park SM, Wong DJ, Ooi CC, et al. (2016) Molecular profiling of single circulating tumor cells from lung cancer patients. Proc Natl Acad Sci USA 113: E8379–E8386.    
  • 58. Shi Q, Qin L, Wei W, et al. (2012) Single-cell proteomic chip for profiling intracellular signaling pathways in single tumor cells. Proc Natl Acad Sci USA 109: 419–424.    
  • 59. Byrd TFt, Hoang LT, Kim EG, et al. (2014) The microfluidic multitrap nanophysiometer for hematologic cancer cell characterization reveals temporal sensitivity of the calcein-AM efflux assay. Sci Rep 4: 5117.
  • 60. Nguyen TA, Yin TI, Reyes D, et al. (2013) Microfluidic chip with integrated electrical cell-impedance sensing for monitoring single cancer cell migration in three-dimensional matrixes. Anal Chem 85: 11068–11076.    
  • 61. Buxbaum AR, Yoon YJ, Singer RH, et al. (2015) Single-molecule insights into mRNA dynamics in neurons. Trends Cell Biol 25: 468–475.
  • 62. Schmidt F, Efferth T (2016) Tumor heterogeneity, single-cell sequencing, and drug resistance. Pharmaceuticals 9: 33.    


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Copyright Info: 2017, Min Zhang;Youming Zhang, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

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