Advertisement

Roles of Single Cell Systems Biomedicine in Lung Diseases

  • Yiming Zeng
  • Xiaoyang Chen
  • Xiangdong WangEmail author
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 1068)

Abstract

Single cell sequencing is important to detect the gene heterogeneity between cells, as the part of single-cell systems biology which combines computational science, mathematical modelling and high-throughput technologies with biological function and organization in the cell. We initially arise the question how to integrate the outcomes of single-cell systems biology with clinical phenotype, interpret alterations of single-cell gene sequencing and function in patient response to therapies, and understand the significance of single-cell systems biology in the discovery and development of new molecular diagnostics and therapeutics. The present review furthermore focuses the significance of singe cell systems biology in respiratory diseases and calls the special attention from scientists who are working on single cell systems biology to improve the diagnosis and therapy for patients with lung diseases.

Keywords

Single cell Lung Cancer COPD Diagnosis 

References

  1. 1.
    Wang X (2016) New biomarkers and therapeutics can be discovered during COPD-lung cancer transition. Cell Biol Toxicol 32(5):359–361.  https://doi.org/10.1007/s10565-016-9350-0CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Liu X, Cho WC (2017) Precision medicine in immune checkpoint blockade therapy for non-small cell lung cancer. Clin Transl Med 6(1):7.  https://doi.org/10.1186/s40169-017-0136-7CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Reddy KP, Kong CY, Hyle EP, Baggett TP, Huang M, Parker RA et al (2017) Lung Cancer mortality associated with smoking and smoking cessation among people living with HIV in the United States. JAMA Intern Med 177(11):1613–1621.  https://doi.org/10.1001/jamainternmed.2017.4349CrossRefPubMedGoogle Scholar
  4. 4.
    Fang X, Netzer M, Baumgartner C, Bai C, Wang XD (2013) Genetic network and gene set enrichment analysis to identify biomarkers related to cigarette smoking and lung cancer. Cancer Treat Rev 39(1):77–88CrossRefPubMedGoogle Scholar
  5. 5.
    Niu F, Wang DC, Lu J, Wu W, Wang X (2016) Potentials of single-cell biology in identification and validation of disease biomarkers. J Cell Mol Med 20(9):1789–1795.  https://doi.org/10.1111/jcmm.12868CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Wang W, Zhu B, Wang X (2017) Dynamic phenotypes: illustrating a single-cell odyssey. Cell Biol Toxicol 33(5):423–427.  https://doi.org/10.1007/s10565-017-9400-2CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Lawson MJ, Camsund D, Larsson J, Baltekin Ö, Fange D, Elf J (2017) In situ genotyping of a pooled strain library after characterizing complex phenotypes. Mol Syst Biol 13(10):947.  https://doi.org/10.15252/msb.20177951CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Liu H, Dong P, Ioannou MS, Li L, Shea J, Pasolli HA, et al (2017) Visualizing long-term single-molecule dynamics in vivo by stochastic protein labeling. Proc Natl Acad Sci U S A. 115(2):343–348. 201713895.  https://doi.org/10.1073/pnas.1713895115CrossRefGoogle Scholar
  9. 9.
    Zhao H, Adler KB, Bai C, Tang F, Wang X (2006) Epithelial proteomics in multiple organs and tissues: similarities and variations between cells, organs, and diseases. J Proteome Res 5(4):743–755CrossRefPubMedGoogle Scholar
  10. 10.
    Wang XD (2015) In: Wang XD (ed) Single Cell Sequencing and Systems Immunology, Translational bioinformatics, vol 5. Springer, Dordrecht.  https://doi.org/10.1007/978-94-017-9753-5CrossRefGoogle Scholar
  11. 11.
    Zhang D, Wang X (2015) A simple protocol for single lung cancer cell isolation-making the single cell based lung cancer research feasible for individual investigator. In: Wang X (ed) Single cell sequencing and systems immunology, vol 5. Springer Netherlands, Dordrecht, pp 165–174Google Scholar
  12. 12.
    Wang J, Min Z, Jin M, Wang X (2015) Protocol for single cell isolation by flow cytometry. In: Wang X (ed) Single cell sequencing and systems immunology, vol 5. Springer Netherlands, Dordrecht, pp 155–163Google Scholar
  13. 13.
    Wang W, Gao D, Wang X (2017) Can single-cell RNA sequencing crack the mystery of cells? Cell Biol Toxicol 34(1):1–6.  https://doi.org/10.1007/s10565-017-9404-yCrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Kim KT, Lee HW, Lee HO, Kim SC, Seo YJ, et al (2015) Single-cell mRNA sequencing identifies subclonal heterogeneity in anti-cancer drug responses of lung adenocarcinoma cells. Genome Biol. 16(1):127. Published online 2015 19.  https://doi.org/10.1186/s13059-015-0692-3
  15. 15.
    McGranahan N, Swanton C (2017) Cancer evolution constrained by the immune microenvironment. Cell 170(5):825–827.  https://doi.org/10.1016/j.cell.2017.08.012CrossRefPubMedGoogle Scholar
  16. 16.
    Wang W, Wang X (2017) Single-cell CRISPR screening in drug resistance. Cell Biol Toxicol 33(3):207–210.  https://doi.org/10.1007/s10565-017-9396-7CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Treutlein B, Brownfield DG, Wu AR, Neff NF, Mantalas GL, Espinoza FH et al (2014) Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq. Nature 509(7500):371–375.  https://doi.org/10.1038/nature13173CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Wang DC, Wang W, Zhu B, Wang X (2018) Lung Cancer heterogeneity and new strategies for drug therapy. Annu Rev Pharmacol Toxicol 58:531–546.  https://doi.org/10.1146/annurev-pharmtox-010716-104523CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Suzuki A, Matsushima K, Makinoshima H, Sugano S, Kohno T, Tsuchihara K, Suzuki Y (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.  https://doi.org/10.1186/s13059-015-0636-yCrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Ellsworth DL, Blackburn HL, Shriver CD, Rabizadeh S, Soon-Shiong P, Ellsworth RE (2017) Single-cell sequencing and tumorigenesis: improved understanding of tumor evolution and metastasis. Clin Transl Med 6(1):15.  https://doi.org/10.1186/s40169-017-0145-6CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Chu MP, Kriangkum J, Venner CP, Sandhu I, Hewitt J, Belch AR, Pilarski LM. Addressing heterogeneity of individual blood cancers: the need for single cell analysis. Cell Biol Toxicol. 2017 Apr;33(2):83–97. doi: 10.1007/s10565-016-9367-4.CrossRefPubMedGoogle Scholar
  22. 22.
    Shi L, Dong N, Ji D, Huang X, Ying Z, Wang X, Chen C (2017) Lipopolysaccharide-induced CCN1 production enhances interleukin-6 secretion in bronchial epithelial cells. Cell Biol Toxicol.:1–11.  https://doi.org/10.1007/s10565-017-9401-1
  23. 23.
    Wang X, Adler KB, Erjefalt J, Bai CB (2007) Role of airway epithelial dysfunction in development of acute lung injury and acute respiratory distress syndrome. Expert Rev Respir Med 1(1):149–155.  https://doi.org/10.1586/17476348.1.1.149CrossRefPubMedGoogle Scholar
  24. 24.
    Shi L, Dong N, Fang XC, Wang XD (2016) Regulatory mechanisms of TGF-β1-induced fibrogenesis of human alveolar epithelial cells. J Cell Mol Med 20(11):2183–2193.  https://doi.org/10.1111/jcmm.12918. Epub 2016 Jul 15CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Vaughan AE, Brumwell AN, Xi Y, Gotts JE, Brownfield DG, Treutlein B et al (2015) Lineage-negative progenitors mobilize to regenerate lung epithelium after major injury. Nature 517(7536):621–625.  https://doi.org/10.1038/nature14112CrossRefPubMedGoogle Scholar
  26. 26.
    Xu Y, Mizuno T, Sridharan A, Du Y, Guo M, Tang J et al (2016) Single-cell RNA sequencing identifies diverse roles of epithelial cells in idiopathic pulmonary fibrosis. JCI Insight 1(20):e90558CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Kao FS, Pan YR, Hsu RQ, Chen HM (2012) Efficacy verification and microscopic observations of an anticancer peptide, CB1a, on single lung cancer cell. Biochim Biophys Acta 1818(12):2927–2935.  https://doi.org/10.1016/j.bbamem.2012.07.019CrossRefPubMedGoogle Scholar
  28. 28.
    Villarini M1, Scassellati-Sforzolini G, Moretti M, Pasquini R (2000) In vitro genotoxicity of terbutryn evaluated by the alkaline single-cell microgel-electrophoresis “comet” assay. Cell Biol Toxicol 16(5):285–292CrossRefGoogle Scholar
  29. 29.
    Taira Z, Yamase D, Ueda Y (2007) A new technique for assaying cytochrome P450 enzyme activity in a single cell. Cell Biol Toxicol 23(3):143–151CrossRefPubMedGoogle Scholar
  30. 30.
    Du Y, Guo M (2015) Whitsett JA, et al. ‘LungGENS’: a web-based tool for mapping single-cell gene expression in the developing lung. Thorax 70:1092–1094CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    Du Y, Kitzmiller JA, Sridharan A, Ak P, Bridges JP, Misra PS et al (2017) Lung gene expression analysis (LGEA): an integrative web portal for comprehensive gene expression data analysis in lung development. Thorax 72(5):481–484.  https://doi.org/10.1136/thoraxjnl-2016-209598CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Guo M, Wang H, Potter SS et al (2015) SINCERA: a pipeline for single-cell RNA-Seq profiling analysis. PLoS Comput Biol 11:e1004575.  https://doi.org/10.1371/journal.pcbi.1004575CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Datlinger P, Rendeiro AF, Schmidl C, Krausgruber T, Traxler P, Klughammer J et al (2017) Pooled CRISPR screening with single-cell transcriptome readout. Nat Methods 14(3):297–301.  https://doi.org/10.1038/nmeth.4177CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Fang H, Wang W (2016) Could CRISPR be the solution for gene editing’s Gordian knot? Cell Biol Toxicol 32(6):465–467CrossRefPubMedGoogle Scholar
  35. 35.
    Sakuma T, Yamamoto T (2017) Magic wands of CRISPR-lots of choices for gene knock-in. Cell Biol Toxicol 33(6):501–505.  https://doi.org/10.1007/s10565-017-9409-6CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Guernet A, Mungamuri SK, Cartier D, Sachidanandam R, Jayaprakash A, Adriouch S et al (2016) CRISPR-barcoding for Intratumor genetic heterogeneity modeling and functional analysis of oncogenic driver mutations. Mol Cell 63(3):526–538.  https://doi.org/10.1016/j.molcel.2016.06.017CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Park S, Zhang X, Li C, Yin C, Li J, Fallon JT et al (2017) Single-cell RNA sequencing reveals an altered gene expression pattern as a result of CRISPR/cas9-mediated deletion of gene 33/Mig6 and chronic exposure to hexavalent chromium in human lung epithelial cells. Toxicol Appl Pharmacol 330:30–39.  https://doi.org/10.1016/j.taap.2017.07.003CrossRefPubMedPubMedCentralGoogle Scholar
  38. 38.
    Castillo A (2016) Gene editing using CRISPR-Cas9 for the treatment of lung cancer. Colomb Med (Cali) 47(4):178–180Google Scholar
  39. 39.
    Tang H, Shrager JB (2016) CRISPR/Cas-mediated genome editing to treat EGFR-mutant lung cancer: a personalized molecular surgical therapy. EMBO Mol Med 8(2):83–85.  https://doi.org/10.15252/emmm.201506006CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Paes BCMF, Moço PD, Pereira CG, Porto GS, de Sousa Russo EM et al (2017) Ten years of iPSC: clinical potential and advances in vitro hematopoietic differentiation. Cell Biol Toxicol 33(3):233–250.  https://doi.org/10.1007/s10565-016-9377-2. Epub 2016 Dec 30CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Respiratory Pulmonary and Critical Care MedicineThe Second Hospital of Fujian Medical UniversityQuanzhouChina

Personalised recommendations