Collagen Signaling via DDR1 Exacerbates Barriers to Macromolecular Drug Delivery in a 3D Model of Pancreatic Cancer Fibrosis

Fibrosis is a significant barrier to drug delivery in pancreatic ductal adenocarcinoma (PDAC) and contributes to its dismal prognosis. Pancreatic stellate cells (PSCs) drive fibrosis by excessively secreting extracellular matrix proteins such as collagen I. Collagen I is thought to physically obstruct the delivery of macromolecules, such as albumin, antibodies, and nanomedicines. Apart from its structural role, collagen signals through dedicated cell surface receptors, such as the discoidin domain receptors (DDR) 1/2. However, whether and how collagen signaling contributes to fibrotic barrier generation remains uncharacterized. Here, a 3D culture model of PDAC fibrosis constructed from patient PSCs is used to assess the contribution of DDR1/2-mediated collagen signaling. DDR1/2 inhibition diminishes collagen I expression in PSCs to enhance macromolecular delivery. Moreover, MEK inhibitors exacerbate the fibrotic barrier by up-regulating collagen I, an effect reversed by inhibiting DDR1/2. Through isoform-specific targeting, inhibiting DDR1, but not DDR2, is shown to be effective. Downstream of DDR, the involvement of the PI3K/AKT/mTOR pathway is demonstrated, particularly alternative mTOR complexes involving MEAK7 and GIT1. Altogether, the results show in vitro that DDR1-mediated collagen signaling exacerbates the fibrotic barrier and may be targeted to enhance macromolecular drug delivery in PDAC.

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Journal
Small
Published
2025-10-31
DOI
https://doi.org/10.1002/smll.202506926
Citations
1
Primary Topic
Cell Adhesion Molecules Research
Type
article
Field-Weighted Citation Impact
1.62
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article

Collagen Signaling via DDR1 Exacerbates Barriers to Macromolecular Drug Delivery in a 3D Model of Pancreatic Cancer Fibrosis

Mayu Ohira, Shinichi Toyooka, Hiroyuki Iwasaki, Kensuke Osada et al.
1 citations
Small
Cell Adhesion Molecules Research
1.62
article

Collagen Signaling via DDR1 Exacerbates Barriers to Macromolecular Drug Delivery in a 3D Model of Pancreatic Cancer Fibrosis

Mayu Ohira, Shinichi Toyooka, Hiroyuki Iwasaki, Kensuke Osada, Takuya Nakazawa, Atsushi Masamune, Miho Kitamura, Hiroyoshi Y. Tanaka, Horacio Cabral, Hirohiko Tsujii, Akihiro Nishiguchi, Ryuji Nakamura, Mitsunobu R. Kano, Masaya Yamamoto, Haruko Ohta‐Okano
article en
1 citations

Abstract

Fibrosis is a significant barrier to drug delivery in pancreatic ductal adenocarcinoma (PDAC) and contributes to its dismal prognosis. Pancreatic stellate cells (PSCs) drive fibrosis by excessively secreting extracellular matrix proteins such as collagen I. Collagen I is thought to physically obstruct the delivery of macromolecules, such as albumin, antibodies, and nanomedicines. Apart from its structural role, collagen signals through dedicated cell surface receptors, such as the discoidin domain receptors (DDR) 1/2. However, whether and how collagen signaling contributes to fibrotic barrier generation remains uncharacterized. Here, a 3D culture model of PDAC fibrosis constructed from patient PSCs is used to assess the contribution of DDR1/2-mediated collagen signaling. DDR1/2 inhibition diminishes collagen I expression in PSCs to enhance macromolecular delivery. Moreover, MEK inhibitors exacerbate the fibrotic barrier by up-regulating collagen I, an effect reversed by inhibiting DDR1/2. Through isoform-specific targeting, inhibiting DDR1, but not DDR2, is shown to be effective. Downstream of DDR, the involvement of the PI3K/AKT/mTOR pathway is demonstrated, particularly alternative mTOR complexes involving MEAK7 and GIT1. Altogether, the results show in vitro that DDR1-mediated collagen signaling exacerbates the fibrotic barrier and may be targeted to enhance macromolecular drug delivery in PDAC.

SmallVol. 21(50)
Okayama University (JP), Tohoku University (JP), National Institute for Materials Science (JP), National Institutes for Quantum Science and Technology (JP), The University of Tokyo (JP)
Openalex Percentile: Top 14%
Cell Adhesion Molecules Research
1.62
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