Evidence map›Paper›PMID 42436584›Full record

ArticleGenome biology2026

TIPs: a deep learning-guided proteogenomic framework to expand the landscape of transposable element-derived antigens with immunopeptidomics.

Qian Wu, Xinyue Zhou, Qizhen Feng, Zixiang Shang, Jiayi Shen, Xiaoxiang Huang, Xiaobing Liu, Wenguang Shao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome biology, 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

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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

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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

8 authors.

Qian WuState Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, Sheng Yushou Center of Cell Biology and Immunology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China.
Xinyue ZhouState Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, Sheng Yushou Center of Cell Biology and Immunology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China.
Qizhen FengState Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, Sheng Yushou Center of Cell Biology and Immunology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China.
Zixiang ShangState Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, Sheng Yushou Center of Cell Biology and Immunology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China.
Jiayi ShenState Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, Sheng Yushou Center of Cell Biology and Immunology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China.
Xiaoxiang HuangState Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, Sheng Yushou Center of Cell Biology and Immunology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China.
Xiaobing LiuDepartment of Vascular Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, People's Republic of China.
Wenguang ShaoState Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, Sheng Yushou Center of Cell Biology and Immunology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China. wshao@sjtu.edu.cn.ORCID https://orcid.org/0000-0003-0905-0728

Funding

National Key Research and Development Program of China 2022YFC3401600National Natural Science Foundation of China 32271493 and 62102248National Natural Science Foundation of China 325B1014
6 · The paper itself

Abstract

Transposable elements (TEs) represent an abundant and important source of HLA-presented antigens, but their immunopeptidomic characterization remains challenging due to the inflated search space. We present TIPs (TE-derived Immunopeptidomic Search), a deep learning-guided proteogenomic framework that integrates de novo sequencing, database refinement, multiple search engines and stringent FDR controls. Across various cell lines and cancer types, TIPs identified 20-fold more TE-derived peptides on average than conventional approaches. It further revealed many recurrent, tumor-specific antigens from TEs, including candidates induced by epigenetic therapy. These findings highlight the potential of TIPs to expand the antigenic landscape beyond canonical sources.

Indexed as

Antigens, NeoplasmDeep LearningDNA Transposable ElementsProteogenomicsHumansPeptidesProteomicsAntigens, NeoplasmDNA Transposable ElementsPeptidesImmunopeptidomicsMass spectrometryProteomicsTransposable elementsTumor antigens

Identifiers

PMID42436584
PMCPMC13440072

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Registered trials

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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.