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SCIENCE CHINA Life Sciences, Volume 64 , Issue 7 : 1097-1115(2021) https://doi.org/10.1007/s11427-020-1739-6

Construction of chlorogenic acid-containing liposomes with prolonged antitumor immunity based on T cell regulation

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  • ReceivedApr 28, 2020
  • AcceptedJul 10, 2020
  • PublishedSep 29, 2020

Abstract


Acknowledgment

We are grateful for the financial support from the National Megaproject for Innovative Drugs (2018ZX09711001 and 2018ZX09721003) of the Chinese government, Graduate Student Innovation Fund of PUMC (2018-1007-01) as well as CAMS Innovation Fund for Medical Sciences (CIFMS- 2019-I2M-1-005).


Interest statement

The author(s) declare that they have no conflict of interest.


Supplement

SUPPORTING INFORMATION

The supporting information is available online at https://doi.org/10.1007/s11427-020-1739-6. The supporting materials are published as submitted, without typesetting or editing. The responsibility for scientific accuracy and content remains entirely with the authors.


References

[1] AlQahtani A.D., O’Connor D., Domling A., Goda S.K.. Strategies for the production of long-acting therapeutics and efficient drug delivery for cancer treatment. Biomed Pharmacother, 2019, 113: 108750 CrossRef PubMed Google Scholar

[2] Bahrami A., Fereidouni M., Pirro M., Bianconi V., Sahebkar A.. Modulation of regulatory T cells by natural products in cancer. Cancer Lett, 2019, 459: 72-85 CrossRef PubMed Google Scholar

[3] Bhattacharyya S., Majhi S., Saha B.P., Mukherjee P.K.. Chlorogenic acid–phospholipid complex improve protection against UVA induced oxidative stress. J Photochem Photobiol B Biol, 2014, 130: 293-298 CrossRef PubMed Google Scholar

[4] Bozó T., Mészáros T., Mihály J., Bóta A., Kellermayer M.S.Z., Szebeni J., Kálmán B.. Aggregation of PEGylated liposomes driven by hydrophobic forces. Colloids Surfs B-Biointerfaces, 2016, 147: 467-474 CrossRef PubMed Google Scholar

[5] Budryn G., Pałecz B., Rachwał-Rosiak D., Oracz J., Zaczyńska D., Belica S., Navarro-González I., Meseguer J.M.V., Pérez-Sánchez H.. Effect of inclusion of hydroxycinnamic and chlorogenic acids from green coffee bean in β-cyclodextrin on their interactions with whey, egg white and soy protein isolates. Food Chem, 2015, 168: 276-287 CrossRef PubMed Google Scholar

[6] Celia C., Trapasso E., Cosco D., Paolino D., Fresta M.. Turbiscan Lab® Expert analysis of the stability of ethosomes® and ultradeformable liposomes containing a bilayer fluidizing agent. Colloids Surfs B Biointerfaces, 2009, 72: 155-160 CrossRef PubMed Google Scholar

[7] dos Santos M.D., Martins P.R., dos Santos P.A., Bortocan R., Iamamoto Y., Lopes N.P.. Oxidative metabolism of 5-o-caffeoylquinic acid (chlorogenic acid), a bioactive natural product, by metalloporphyrin and rat liver mitochondria. Eur J Pharm Sci, 2005, 26: 62-70 CrossRef PubMed Google Scholar

[8] Du J., Liang Z., Xu J., Zhao Y., Li X., Zhang Y., Zhao D., Chen R., Liu Y., Joshi T., et al. Plant-derived phosphocholine facilitates cellular uptake of anti-pulmonary fibrotic HJT-sRNA-m7. Sci China Life Sci, 2019, 62: 309-320 CrossRef PubMed Google Scholar

[9] Eloy J.O., Claro de Souza M., Petrilli R., Barcellos J.P.A., Lee R.J., Marchetti J.M.. Liposomes as carriers of hydrophilic small molecule drugs: Strategies to enhance encapsulation and delivery. Colloids Surfs B Biointerfaces, 2014, 123: 345-363 CrossRef PubMed Google Scholar

[10] Feng Y., Sun C., Yuan Y., Zhu Y., Wan J., Firempong C.K., Omari-Siaw E., Xu Y., Pu Z., Yu J., et al. Enhanced oral bioavailability and in vivo antioxidant activity of chlorogenic acid via liposomal formulation. Int J Pharm, 2016, 501: 342-349 CrossRef PubMed Google Scholar

[11] Fleetwood A.J., Dinh H., Cook A.D., Hertzog P.J., Hamilton J.A.. GM-CSF- and M-CSF-dependent macrophage phenotypes display differential dependence on type I interferon signaling. J Leukocyte Biol, 2009, 86: 411-421 CrossRef PubMed Google Scholar

[12] Gharib R., Greige-Gerges H., Fourmentin S., Charcosset C., Auezova L.. Liposomes incorporating cyclodextrin–drug inclusion complexes: Current state of knowledge. Carbohydrate Polyms, 2015, 129: 175-186 CrossRef PubMed Google Scholar

[13] He H., Lu Y., Qi J., Zhu Q., Chen Z., Wu W.. Adapting liposomes for oral drug delivery. Acta Pharm Sin B, 2019, 9: 36-48 CrossRef PubMed Google Scholar

[14] Henriksen-Lacey M., Bramwell V.W., Christensen D., Agger E.M., Andersen P., Perrie Y.. Liposomes based on dimethyldioctadecylammonium promote a depot effect and enhance immunogenicity of soluble antigen. J Control Release, 2010, 142: 180-186 CrossRef PubMed Google Scholar

[15] Huang S., Wang L.L., Xue N.N., Li C., Guo H.H., Ren T.K., Zhan Y., Li W.B., Zhang J., Chen X.G., et al. Chlorogenic acid effectively treats cancers through induction of cancer cell differentiation. Theranostics, 2019, 9: 6745-6763 CrossRef PubMed Google Scholar

[16] Kumar B.V., Connors T.J., Farber D.L.. Human T cell development, localization, and function throughout life. Immunity, 2018, 48: 202-213 CrossRef PubMed Google Scholar

[17] Li Y., Ren X., Lio C., Sun W., Lai K., Liu Y., Zhang Z., Liang J., Zhou H., Liu L., et al. A chlorogenic acid-phospholipid complex ameliorates post-myocardial infarction inflammatory response mediated by mitochondrial reactive oxygen species in SAMP8 mice. Pharmacol Res, 2018, 130: 110-122 CrossRef PubMed Google Scholar

[18] Marianecci C., Paolino D., Celia C., Fresta M., Carafa M., Alhaique F.. Non-ionic surfactant vesicles in pulmonary glucocorticoid delivery: characterization and interaction with human lung fibroblasts. J Control Release, 2010, 147: 127-135 CrossRef PubMed Google Scholar

[19] Miura C., Li H., Matsunaga H., Haginaka J.. Molecularly imprinted polymer for chlorogenic acid by modified precipitation polymerization and its application to extraction of chlorogenic acid from Eucommia ulmodies leaves. J Pharm Biomed Anal, 2015, 114: 139-144 CrossRef PubMed Google Scholar

[20] Movahedi K., Guilliams M., Van den Bossche J., Van den Bergh R., Gysemans C., Beschin A., De Baetselier P., Van Ginderachter J.A.. Identification of discrete tumor-induced myeloid-derived suppressor cell subpopulations with distinct T cell-suppressive activity. Blood, 2008, 111: 4233-4244 CrossRef PubMed Google Scholar

[21] Nakamura H., Abu Lila A.S., Nishio M., Tanaka M., Ando H., Kiwada H., Ishida T.. Intra-tumor distribution of PEGylated liposome upon repeated injection: No possession by prior dose. J Control Release, 2015, 220: 406-413 CrossRef PubMed Google Scholar

[22] Nallamuthu I., Devi A., Khanum F.. Chlorogenic acid loaded chitosan nanoparticles with sustained release property, retained antioxidant activity and enhanced bioavailability. Asian J Pharm Sci, 2015, 10: 203-211 CrossRef Google Scholar

[23] Shafabakhsh R., Pourhanifeh M.H., Mirzaei H.R., Sahebkar A., Asemi Z., Mirzaei H.. Targeting regulatory T cells by curcumin: A potential for cancer immunotherapy. Pharmacol Res, 2019, 147: 104353 CrossRef PubMed Google Scholar

[24] Signorell R.D., Luciani P., Brambilla D., Leroux J.C.. Pharmacokinetics of lipid-drug conjugates loaded into liposomes. Eur J Pharm Biopharm, 2018, 128: 188-199 CrossRef PubMed Google Scholar

[25] Stupp R., Mason W.P., van den Bent M.J., Weller M., Fisher B., Taphoorn M.J.B., Belanger K., Brandes A.A., Marosi C., Bogdahn U., et al. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med, 2005, 352: 987-996 CrossRef PubMed Google Scholar

[26] Tesi R.J.. MDSC; the most important cell you have never heard of. Trends Pharmacol Sci, 2019, 40: 4-7 CrossRef PubMed Google Scholar

[27] Tian M., Shi Y., Liu W., Fan J.. Immunotherapy of hepatocellular carcinoma: strategies for combinatorial intervention. Sci China Life Sci, 2019, 62: 1138-1143 CrossRef PubMed Google Scholar

[28] Wang B., Li Q., Qin L., Zhao S., Wang J., Chen X.. Transition of tumor-associated macrophages from MHC class IIhi to MHC class IIlow mediates tumor progression in mice. BMC Immunol, 2011, 12: 43 CrossRef PubMed Google Scholar

[29] Wang C., Liu P., Zhuang Y., Li P., Jiang B., Pan H., Liu L., Cai L., Ma Y.. Lymphatic-targeted cationic liposomes: a robust vaccine adjuvant for promoting long-term immunological memory. Vaccine, 2014, 32: 5475-5483 CrossRef PubMed Google Scholar

[30] Wan D., Yang Y., Liu Y., Cun X., Li M., Xu S., Zhao W., Xiang Y., Qiu Y., Yu Q., et al. Sequential depletion of myeloid-derived suppressor cells and tumor cells with a dual-pH-sensitive conjugated micelle system for cancer chemoimmunotherapy. J Control Release, 2020, 317: 43-56 CrossRef PubMed Google Scholar

[31] Xiang Z., Ning Z.. Scavenging and antioxidant properties of compound derived from chlorogenic acid in South-China honeysuckle. LWT - Food Sci Technol, 2008, 41: 1189-1203 CrossRef Google Scholar

[32] Xue N., Zhou Q., Ji M., Jin J., Lai F., Chen J., Zhang M., Jia J., Yang H., Zhang J., et al. Chlorogenic acid inhibits glioblastoma growth through repolarizating macrophage from M2 to M1 phenotype. Sci Rep, 2017, 7: 39011 CrossRef PubMed ADS Google Scholar

[33] Yang Q., Lai S.K.. Anti-PEG immunity: emergence, characteristics, and unaddressed questions. WIREs Nanomed Nanobiotechnol, 2015, 7: 655-677 CrossRef PubMed Google Scholar

[34] Yang Y., Yang Y., Xie X., Cai X., Zhang H., Gong W., Wang Z., Mei X.. PEGylated liposomes with NGR ligand and heat-activable cell-penetrating peptide–doxorubicin conjugate for tumor-specific therapy. Biomaterials, 2014, 35: 4368-4381 CrossRef PubMed Google Scholar

[35] Youn J.I., Nagaraj S., Collazo M., Gabrilovich D.I.. Subsets of myeloid-derived suppressor cells in tumor-bearing mice. J Immunol, 2008, 181: 5791-5802 CrossRef PubMed Google Scholar

[36] Zhang J., Wang Z., Li Y., Liu Y., Cai W., Li C., Lu J., Qiao Y.. A strategy for comprehensive identification of sequential constituents using ultra-high-performance liquid chromatography coupled with linear ion trap-Orbitrap mass spectrometer, application study on chlorogenic acids in Flos Lonicerae Japonicae. Talanta, 2016, 147: 16-27 CrossRef PubMed Google Scholar

[37] Zhang Q., Li J., Wang C., Sun W., Zhang Z., Cheng W.. A gradient HPLC method for the quality control of chlorogenic acid, linarin and luteolin in Flos Chrysanthemi Indici suppository. J Pharm Biomed Anal, 2007, 43: 753-757 CrossRef PubMed Google Scholar

[38] Zhuang Y., Ma Y., Wang C., Hai L., Yan C., Zhang Y., Liu F., Cai L.. PEGylated cationic liposomes robustly augment vaccine-induced immune responses: Role of lymphatic trafficking and biodistribution. J Control Release, 2012, 159: 135-142 CrossRef PubMed Google Scholar

  • Figure 1

    Schemes on preparation and drug administration of CHA-PC loaded liposomes.

  • Figure 2

    (Color online) Transmission and backscattering profiles of CPL (A) and CPPL (B) in solutions simulating the in vivo environment (90% MEM+10% FBS) by using Turbiscan Lab Expert. Data are reported as a function of time (0–24 h) and sample height (from 8 to 29 mm).

  • Figure 3

    Mean plasma concentration-time curves (A) of free CHA, CPL and CPPL after intravenous injection in rats (mean±SD, 10 mg kg–1,n=5); In vivo biodistribution of DiR, DiR Lipo and DiR PEG-Lipo in mice bearing G422 mouse glioma cells: (B) The whole body imaging at different time points after systemic administration; (C) Fluorescence detection of isolated main tissues and organs from mice at the end point of observation.

  • Figure 4

    In vivo antitumor study of various formulations containing CHA in G422 mouse glioma cells in female ICR mice after intravenous injection. The results are presented as the means±SD. A, Photograph of the solid tumors removed from different treatment groups at the study termination. B, The weights of the removed tumors (n=6), *P<0.05, **P<0.01, ***P<0.001; C, Spleen index of different treatment groups at the study termination (n=6), *P<0.05, **P<0.01, ***P<0.001. D, Histological examinations of tumors from different treatment groups at the study termination using H&E staining. Herein blood vessels and apoptotic cell regions are pointed out by red and black arrows, respectively.

  • Figure 5

    (Color online) Tumor infiltrating immune cells in each treatment group (*P<0.05, **P<0.01, ***P<0.001). A, Immunohistochemistry images of CD3+ T cells infiltrating in tumors removed from different treatment groups. B, Infiltration of CD3+ T cells in tumor tissues, lymph node and blood detected by flow cytometry. C, The logical order analysis of T cells in TME, lymph node as well as blood investigated by flow cytometry. D, The corresponding immune cells of CD8+ T cells in tumor tissues, lymph node and blood, respectively. E, The corresponding immune cells of CD4+ T cells in tumor tissues, lymph node and blood, respectively.

  • Figure 6

    (Color online) The effect of CHA-containing formulations on memory T cells in the tumor tissue, lymph node and blood of different treatment groups (*P<0.05, **P<0.01, ***P<0.001). A, Frequency of TEM cells (CD44+CD62LCD45+) in the tumor tissue, lymph node and blood, respectively. B, Frequency of TCM cells (CD44+CD62L+ CD45+) in the tumor tissue, lymph node and blood, respectively.

  • Figure 7

    (Color online) Expression of macrophage, M1-like phenotype, M2-like phenotype in tumor tissue (A) and spleen (B) from different treatment groups. The expression of MHC II in tumor and spleen tissues were evaluated by flow cytometry (C) and the histogram bars represent three independent experiments (D).

  • Figure 8

    MDSCs infiltration in tumor tissue and spleen in each treatment group (*P<0.05, **P<0.01, ***P<0.001). A, Immunohistochemistry images of MDSCs expressed in tumor tissue removed from different treatment groups. B, MDSCs levels in tumor tissue and spleen from different treatment groups detected by flow cytometry.

  • Figure 9

    (Color online) Secretion levels of Th1 related cytokines (IFN-γ and IL12p70) and Th2 related cytokines (IL-10 and TGF-β) in tumor tissue and spleen from different treatment groups. Data are represented as the means±standard deviation, n=6, **P<0.05, **P<0.01, ***P<0.001.

  • Figure 10

    (Color online) Diagrammatic presentation of in vivo antitumor immune mechanism of CPPL and CPL.

  • Table 1   Storage stability of CPL and CPPL at 4°C (n=3)

    Time (day)

    Characterization

    CPL

    CPPL

    0

    Particle size (nm)

    220.37±0.75

    149.73±0.50

    PDI

    0.338±0.007

    0.279±0.006

    Zeta potential (mV)

    –9.76±0.28

    –20.14±0.20

    EE (%)

    60.5±0.35

    60.46±0.72

    1

    Particle size (nm)

    221.80±1.15

    155.93±1.14

    PDI

    0.388±0.004

    0.27±0.015

    Zeta potential (mV)

    –7.92±0.35

    –17.14±0.83

    EE (%)

    57.66±2.34

    57.48±3.01

    3

    Particle size (nm)

    227.90±0.86

    146.40±1.42

    PDI

    0.395±0.017

    0.217±0.008

    Zeta potential (mV)

    –7.90±0.38

    –17.02±0.68

    EE (%)

    55.54±4.54

    57.85±2.99

    5

    Particle size (nm)

    229.13±0.33

    150.20±1.27

    PDI

    0.370±0.012

    0.244±0.011

    Zeta potential (mV)

    –8.07±0.05

    –16.01±0.25

    EE (%)

    56.78±3.45

    58.64±1.97

    7

    Particle size (nm)

    229.30±0.86

    151.23±1.87

    PDI

    0.400±0.003

    0.203±0.016

    Zeta potential (mV)

    –7.23±0.32

    –18.89±0.23

    EE (%)

    58.93±1.73

    58.43±2.79

    10

    Particle size (nm)

    223.80±0.71

    150.07±1.33

    PDI

    0.530±0.019

    0.242±0.005

    Zeta potential (mV)

    –8.62±0.12

    –16.12±0.27

    EE (%)

    57.47±2.56

    59.11±1.43

    15

    Particle size (nm)

    227.23±0.81

    151.00±1.06

    PDI

    0.326±0.011

    0.254±0.007

    Zeta potential (mV)

    –7.87±0.14

    –14.77±0.63

    EE (%)

    54.78±5.56

    56.99±4.09

    30

    Particle size (nm)

    230.07±0.48

    151.50±1.66

    PDI

    0.482±0.107

    0.257±0.004

    Zeta potential (mV)

    –8.50±0.77

    –19.32±0.26

    EE (%)

    56.77±3.64

    57.85±3.17

  • Table 1   Storage stability of CPL and CPPL at 4°C (n=3)

    Time (day)

    Characterization

    CPL

    CPPL

    0

    Particle size (nm)

    220.37±0.75

    149.73±0.50

    PDI

    0.338±0.007

    0.279±0.006

    Zeta potential (mV)

    –9.76±0.28

    –20.14±0.20

    EE (%)

    60.5±0.35

    60.46±0.72

    1

    Particle size (nm)

    221.80±1.15

    155.93±1.14

    PDI

    0.388±0.004

    0.27±0.015

    Zeta potential (mV)

    –7.92±0.35

    –17.14±0.83

    EE (%)

    57.66±2.34

    57.48±3.01

    3

    Particle size (nm)

    227.90±0.86

    146.40±1.42

    PDI

    0.395±0.017

    0.217±0.008

    Zeta potential (mV)

    –7.90±0.38

    –17.02±0.68

    EE (%)

    55.54±4.54

    57.85±2.99

    5

    Particle size (nm)

    229.13±0.33

    150.20±1.27

    PDI

    0.370±0.012

    0.244±0.011

    Zeta potential (mV)

    –8.07±0.05

    –16.01±0.25

    EE (%)

    56.78±3.45

    58.64±1.97

    7

    Particle size (nm)

    229.30±0.86

    151.23±1.87

    PDI

    0.400±0.003

    0.203±0.016

    Zeta potential (mV)

    –7.23±0.32

    –18.89±0.23

    EE (%)

    58.93±1.73

    58.43±2.79

    10

    Particle size (nm)

    223.80±0.71

    150.07±1.33

    PDI

    0.530±0.019

    0.242±0.005

    Zeta potential (mV)

    –8.62±0.12

    –16.12±0.27

    EE (%)

    57.47±2.56

    59.11±1.43

    15

    Particle size (nm)

    227.23±0.81

    151.00±1.06

    PDI

    0.326±0.011

    0.254±0.007

    Zeta potential (mV)

    –7.87±0.14

    –14.77±0.63

    EE (%)

    54.78±5.56

    56.99±4.09

    30

    Particle size (nm)

    230.07±0.48

    151.50±1.66

    PDI

    0.482±0.107

    0.257±0.004

    Zeta potential (mV)

    –8.50±0.77

    –19.32±0.26

    EE (%)

    56.77±3.64

    57.85±3.17

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