Evidence map›Paper›PMID 42893987›Full record

ArticleNature communications2026

A lipoprotein-biomimetic nanoplatform for oncogenic KRAS mutation-specific lysosome-targeting protein degradation.

Hang Yang, Xinyi Zhou, Jiafeng Wang, Chenyue Yang, Yuzhao Jin, Xufeng Liao, Xiangrui Liu, Chuansheng Guo, Qian Xiao, Quan Zhou and 1 more

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Hang Yang *Department of Colorectal Surgery and Oncology (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.ORCID 0000-0003-1803-4877
Xinyi Zhou *Department of Colorectal Surgery and Oncology (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. xinyizhou@zju.edu.cn.
Jiafeng Wang *Department of Cell Biology, Zhejiang University School of Medicine, Hangzhou, China.ORCID 0009-0006-8114-6061
Chenyue YangDepartment of Colorectal Surgery and Oncology (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Yuzhao JinDepartment of Colorectal Surgery and Oncology (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Xufeng LiaoDepartment of Colorectal Surgery and Oncology (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Xiangrui LiuCenter for Medical Research and Innovation in Digestive System Tumors, Ministry of Education, Hangzhou, China.ORCID 0000-0003-4960-5847
Chuansheng GuoDepartment of Colorectal Surgery and Oncology (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Qian XiaoDepartment of Colorectal Surgery and Oncology (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. qxiao3@zju.edu.cn.ORCID 0000-0002-0120-2371
Quan ZhouDepartment of Cell Biology, Zhejiang University School of Medicine, Hangzhou, China. quanzhou91@zju.edu.cn.ORCID 0000-0002-6252-0154
Kefeng DingDepartment of Colorectal Surgery and Oncology (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. dingkefeng@zju.edu.cn.ORCID 0000-0002-2380-3717

Funding

National Natural Science Foundation of China (National Science Foundation of China) 82373449
6 · The paper itself

Abstract

Lysosome-targeting protein degradation strategies have evolved to leverage lineage-specific receptors to improve selectivity, yet remain unable to distinguish malignant from normal cells within the same lineage. Since oncogenic mutations are the defining feature of malignant cells, we here develop KRAS-mutated (MT) tumor targeting chimeras (KRASTAC), a lipoprotein-biomimetic nanoplatform that hijacks the enhanced macropinocytosis in KRAS-MT cells for mutation-specific protein degradation. KRASTAC potently degrades diverse proteins including epidermal growth factor receptor and programmed cell death ligand 1 (PD-L1) in KRAS-MT cells at a low antibody concentration of 2.5 nM within 9 h, with minimal impact in KRAS wild-type (WT) cells. Furthermore, KRASTAC exhibits mutation-specific tumor accumulation and protein degradation in vivo. KRASTAC-induced PD-L1 degradation leads to robust antitumor efficacy and reprogramming of the immunosuppressive microenvironment in mice carrying Kras-MT tumors. Our work presents KRASTAC as a potent mutation-specific protein degradation strategy for KRAS-MT cancers and establishes macropinocytosis as a route for lysosome-targeting protein degradation.

Indexed as

LipoproteinsLysosomesProto-Oncogene Proteins p21(ras)AnimalsB7-H1 AntigenBiomimeticsCell Line, TumorErbB ReceptorsFemaleHumansMiceMutationNeoplasmsPinocytosisProteolysisB7-H1 AntigenErbB ReceptorsKRAS protein, humanLipoproteinsProto-Oncogene Proteins p21(ras)

Identifiers

PMID42893987
PMCPMC13677754

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.