Artificial Intelligence-Guided Cancer Engineering for Tumor Normalization Executed by Tumor Lysosomal-Triggered Supramolecular Chiral Peptide

Cancer engineering for tumor normalization offers a promising therapeutic strategy to reverse malignant cells and their supportive tumor microenvironment into a more benign state. Herein, an artificial intelligence (AI) approach was developed using mRNA data from patients with lung adenocarcinoma to facilitate the identification of aberrant signaling pathways, specifically focusing on PD-L1, Wnt, and macropinocytosis. Targeting these characteristics, we have developed a supramolecular construct called cancer corrector (CCtor) with the aim of harnessing the enhanced macropinocytosis observed in cancer cells. Undergoing cleavage and subsequent drug release triggered by the lysosomal protease in cancer cells, CCtor rectifies the aberrant hyperactivity of both Wnt and PD-L1 signaling pathways. This dual-action therapeutic strategy not only restores normalcy to cancer cells but also exerts an exceptionally robust therapeutic effect. This work exemplifies a future direction for cancer therapies by combining AI with molecular engineering to significantly improve patient outcomes through tumor behavior normalization.

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Publication Details

Journal
ACS Nano
Published
2025-04-29
DOI
https://doi.org/10.1021/acsnano.4c14264
Primary Topic
Chemical Synthesis and Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Artificial Intelligence-Guided Cancer Engineering for Tumor Normalization Executed by Tumor Lysosomal-Triggered Supramolecular Chiral Peptide

Jingmei Wang, Weiming You, Yanmin Zhang, Wangxiao He et al.
ACS Nano
Chemical Synthesis and Analysis
article

Artificial Intelligence-Guided Cancer Engineering for Tumor Normalization Executed by Tumor Lysosomal-Triggered Supramolecular Chiral Peptide

Jingmei Wang, Weiming You, Yanmin Zhang, Wangxiao He, Jin Yan
article en

Abstract

Cancer engineering for tumor normalization offers a promising therapeutic strategy to reverse malignant cells and their supportive tumor microenvironment into a more benign state. Herein, an artificial intelligence (AI) approach was developed using mRNA data from patients with lung adenocarcinoma to facilitate the identification of aberrant signaling pathways, specifically focusing on PD-L1, Wnt, and macropinocytosis. Targeting these characteristics, we have developed a supramolecular construct called cancer corrector (CCtor) with the aim of harnessing the enhanced macropinocytosis observed in cancer cells. Undergoing cleavage and subsequent drug release triggered by the lysosomal protease in cancer cells, CCtor rectifies the aberrant hyperactivity of both Wnt and PD-L1 signaling pathways. This dual-action therapeutic strategy not only restores normalcy to cancer cells but also exerts an exceptionally robust therapeutic effect. This work exemplifies a future direction for cancer therapies by combining AI with molecular engineering to significantly improve patient outcomes through tumor behavior normalization.

ACS NanoVol. 19(18)
Institute for Stem Cell Biology and Regenerative Medicine (IN), First Affiliated Hospital of Xi'an Jiaotong University (CN), Second Affiliated Hospital of Xi'an Jiaotong University (CN), Xi'an Jiaotong University (CN)
National Natural Science Foundation of China, Xi’an Jiaotong University, National Key Research and Development Program of China, Key Research and Development Projects of Shaanxi Province
Openalex Percentile: Top 92%
Chemical Synthesis and Analysis
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