The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Designing Liposomes To Suppress Extracellular Matrix Expression To Enhance Drug Penetration and Pancreatic Tumor Therapy
Abstract
During pancreatic tumor development, pancreatic stellate cells (PSCs) proliferate exuberantly to secrete extracellular matrix (ECM) in the tumor stroma, which presents major barriers for drug delivery and penetration in tumor tissue. Thus, down-regulating ECM levels via regulation of the PSCs may allow enhanced penetration of therapeutic drugs and thereby enhancing their therapeutic efficacy. To regulate the PSCs, a matrix metalloproteinase-2 (MMP-2) responsive peptide-hybrid liposome (MRPL) was constructed via coassembly of a tailor-designed MMP-2 responsive amphiphilic peptide and phospholipids. By utilizing the MMP-2-rich pathological environment, the pirfenidone (PFD) loaded MRPL (MRPL-PFD) can specifically release PFD at the pancreatic tumor site and down-regulate the multiple components of ECM expressed by the PSCs. This resulted in a significant increase in the penetration of gemcitabine into the tumor tissue and enhanced the efficacy of gemcitabine for pancreatic tumor. Our design tailored for antifibrosis of pancreatic cancer may provide a practical approach to build functional liposomes through supramolecular assembly, and regulation of ECM may be a promising adjuvant therapeutic strategy for pancreatic and other ECM-rich tumors.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Siegel, R. L., Miller, K. D., & Jemal, A. (2016) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21332 · Cited by 16,003
Nanoparticle-Based Medicines: A Review of FDA-Approved Materials and Clinical Trials to Date
Bobo, D., Robinson, K. J., Islam, J., Thurecht, K. J., & Corrie, S. R. (2016) · Pharmaceutical Research · doi:10.1007/s11095-016-1958-5 · Cited by 2,586
Gaggioli, C., Hooper, S., Hidalgo-Carcedo, C., Grosse, R., Marshall, J. F., Harrington, K., & Sahai, E. (2007) · Nature Cell Biology · doi:10.1038/ncb1658 · Cited by 1,589
Wang-Gillam, A., Li, C.-P., Bodoky, G., Dean, A., Shan, Y.-S., Jameson, G., Macarulla, T., Lee, K.-H., Cunningham, D., Blanc, J. F., et al. (2016) · The Lancet · doi:10.1016/s0140-6736(15)00986-1 · Cited by 1,222
The role of stroma in pancreatic cancer: Diagnostic and therapeutic implications
Erkan, M., Hausmann, S., Michalski, C. W., Fingerle, A. A., Dobritz, M., Kleeff, J., & Friess, H. (2012) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/nrgastro.2012.115 · Cited by 662
DuFort, C. C., DelGiorno, K. E., & Hingorani, S. R. (2016) · Gastroenterology · doi:10.1053/j.gastro.2016.03.040 · Cited by 144
Cited by
Pancreatic cancer stroma: an update on therapeutic targeting strategies
Hosein, A. N., Brekken, R. A., & Maitra, A. (2020) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-020-0300-1 · Cited by 950
Engineered nanomedicines with enhanced tumor penetration
Ding, J., Chen, J., Gao, L., Jiang, Z., Zhang, Y., Li, M., Xiao, Q., Lee, S. S., & Chen, X. (2019) · Nano Today · doi:10.1016/j.nantod.2019.100800 · Cited by 420
Self-citationHuang, T.-Y., Huang, G.-L., Zhang, C.-Y., Zhuang, B.-W., Liu, B.-X., Su, L.-Y., Ye, J.-Y., Xu, M., Kuang, M., & Xie, X.-Y. (2020) · Frontiers in Chemistry · doi:10.3389/fchem.2020.00001 · Cited by 361
Multicomponent peptide assemblies
Raymond, D. M., & Nilsson, B. L. (2018) · Chemical Society Reviews · doi:10.1039/c8cs00115d · Cited by 346
Han, X., Li, Y., Xu, Y., Zhao, X., Zhang, Y., Yang, X., Wang, Y., Zhao, R., Anderson, G. J., Zhao, Y., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-05906-x · Cited by 339
Self-citation
Metadata
- Authors
- Ji, T., Lang, J., Wang, J., Cai, R., Zhang, Y., Qi, F., Zhang, L., Zhao, X., Wu, W., Hao, J., Qin, Z., Zhao, Y., & Nie, G.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2017-09-05
- Volume
- 11
- Issue
- 9
- Pages
- 8668-8678
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2746888048
- Cited by
- 222
- References
- 6
- FWCI
- 7.00
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Designing Liposomes To Suppress Extracellular Matrix Expression To Enhance Drug Penetration and Pancreatic Tumor Therapy. https://app.cochat.ai/papers/10.1021/acsnano.7b01026
- The paper
- Ji, T., Lang, J., Wang, J., Cai, R., Zhang, Y., Qi, F., Zhang, L., Zhao, X., Wu, W., Hao, J., Qin, Z., Zhao, Y., & Nie, G. (2017). Designing Liposomes To Suppress Extracellular Matrix Expression To Enhance Drug Penetration and Pancreatic Tumor Therapy. ACS Nano. https://doi.org/10.1021/acsnano.7b01026
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
