Atlas-Guided Nanocarrier Strategies Targeting Spatial NTRK2/MAPK Signaling in EGFR-TKI-Resistant Niches of Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) represents a major therapeutic challenge due to the rapid development of resistance to epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs). Recent evidence highlights that this resistance is driven not only by genetic mutations but also by spatial heterogeneity of tumor microenvironments and compensatory signaling mechanisms. In this review, we propose a "spatial-signaling-intervention" framework with a particular focus on the NTRK2/MAPK signaling axis, which plays dual roles in signaling compensation and immune evasion. By integrating spatial multi-omics, proteomics, and AI-assisted topological modeling, three resistant niches are identified: (1) cancer stemness-enriched zones, (2) MAPK hyperactive islands, and (3) immune-cold regions. Based on this atlas, we design precision nanotherapeutic platforms, including responsive, dual-target, and feedback-loop nanocarriers, to selectively modulate resistant spatial niches. Preclinical validation in patient-derived xenografts and organoid models further demonstrates the translational potential of these strategies. This work provides a conceptual and technological roadmap for overcoming EGFR-TKI resistance in ESCC. Atlas-guided nanocarrier systems offer a promising avenue for spatially targeted and feedback-responsive therapy, highlighting the role of pharmaceutics in advancing precision oncology.

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Publication Details

Journal
Pharmaceutics
Published
2026-01-30
DOI
https://doi.org/10.3390/pharmaceutics18020181
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
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article

Atlas-Guided Nanocarrier Strategies Targeting Spatial NTRK2/MAPK Signaling in EGFR-TKI-Resistant Niches of Esophageal Squamous Cell Carcinoma

Hairui Wang, Xiusen Zhang, Shufen Zhang, Shegan Gao et al.
Pharmaceutics
Single-cell and spatial transcriptomics
article

Atlas-Guided Nanocarrier Strategies Targeting Spatial NTRK2/MAPK Signaling in EGFR-TKI-Resistant Niches of Esophageal Squamous Cell Carcinoma

Hairui Wang, Xiusen Zhang, Shufen Zhang, Shegan Gao, Hao Wang, Wenchao Tang, Qizhi Fu, Xing Jin, Lijun Deng, Xin Zhao
article en

Abstract

Esophageal squamous cell carcinoma (ESCC) represents a major therapeutic challenge due to the rapid development of resistance to epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs). Recent evidence highlights that this resistance is driven not only by genetic mutations but also by spatial heterogeneity of tumor microenvironments and compensatory signaling mechanisms. In this review, we propose a "spatial-signaling-intervention" framework with a particular focus on the NTRK2/MAPK signaling axis, which plays dual roles in signaling compensation and immune evasion. By integrating spatial multi-omics, proteomics, and AI-assisted topological modeling, three resistant niches are identified: (1) cancer stemness-enriched zones, (2) MAPK hyperactive islands, and (3) immune-cold regions. Based on this atlas, we design precision nanotherapeutic platforms, including responsive, dual-target, and feedback-loop nanocarriers, to selectively modulate resistant spatial niches. Preclinical validation in patient-derived xenografts and organoid models further demonstrates the translational potential of these strategies. This work provides a conceptual and technological roadmap for overcoming EGFR-TKI resistance in ESCC. Atlas-guided nanocarrier systems offer a promising avenue for spatially targeted and feedback-responsive therapy, highlighting the role of pharmaceutics in advancing precision oncology.

PharmaceuticsVol. 18(2)
Henan University of Science and Technology (CN), Kunming Institute of Zoology (CN), Henan Academy of Sciences (CN), First Affiliated Hospital of Henan University of Science and Technology (CN), Henan Provincial Center for Disease Control and Prevention (CN)
Openalex Percentile: Top 73%
Single-cell and spatial transcriptomics
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