Evidence map›Paper›PMID 40010763›Full record

ArticleJournal for immunotherapy of cancer2025

Novel post-translational modification learning signature reveals B4GALT2 as an immune exclusion regulator in lung adenocarcinoma.

Pengpeng Zhang, Dingli Wang, Guangyao Zhou, Shuai Jiang, Ge Zhang, Lianmin Zhang, Zhenfa Zhang

Erratum issuedAbstract read
In one paragraph

Article in Journal for immunotherapy of cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 74 papers.

0numbers the graph read from it
0cells of the map it votes in
74citing 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

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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

74 citing papers in PubMed.

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14 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Pengpeng Zhang *Department of Lung Cancer, Tianjin Lung Cancer Center, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.ORCID http://orcid.org/0000-0002-9627-2590
Dingli Wang *Department of Lung Cancer, Tianjin Lung Cancer Center, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Guangyao Zhou *Department of Lung Cancer, Tianjin Lung Cancer Center, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Shuai JiangDepartment of Lung Cancer, Tianjin Lung Cancer Center, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Ge ZhangDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Lianmin ZhangDepartment of Lung Cancer, Tianjin Lung Cancer Center, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China zhangzhenfa@tmu.edu.cn zhanglianmin1031@163.com.
Zhenfa ZhangDepartment of Lung Cancer, Tianjin Lung Cancer Center, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China zhangzhenfa@tmu.edu.cn zhanglianmin1031@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung adenocarcinoma (LUAD) presents significant challenges in prognosis and treatment efficacy evaluation. While post-translational modifications are known to influence tumor progression, their prognostic value in LUAD remains largely unexplored.

methodsWe developed a post-translational modification learning signature (PTMLS) using machine learning techniques, analyzing data from 1231 LUAD patients across seven global cohorts. The signature's efficacy in predicting immunotherapy response was evaluated using 12 immunotherapy cohorts spanning multiple cancer types (n=1201). An in-house LUAD tissue cohort (n=171) was used to validate beta-1,4-galactosyltransferase 2's (B4GALT2's) prognostic significance. The role of B4GALT2 in immune exclusion was investigated through in vivo and in vitro experiments.

resultsThe established PTMLS exhibited exceptional predictive capabilities in LUAD patient outcomes, surpassing the efficacy of 98 existing LUAD prognostic indicators. The system's predictive value was validated across diverse malignancy categories for immunotherapeutic response assessment. From a biological perspective, significant correlations were observed between PTMLS and immunological parameters, whereby elevated PTMLS levels were characterized by attenuated immune responses and immunologically cold neoplastic features. Within the PTMLS framework, B4GALT2 was identified as a crucial molecular component (r=0.82, p<0.05), and its heightened expression was linked to unfavorable clinical outcomes in LUAD cases, particularly in specimens exhibiting CD8-depleted phenotypes. The spatial distribution patterns between B4GALT2 and immune cell populations, specifically CD8+ T lymphocytes and CD20+ B lymphocytes, were elucidated through multiplexed immunofluorescence analysis. Laboratory investigations subsequently established B4GALT2's regulatory influence on LUAD cellular expansion in both laboratory cultures and animal models. Significantly, suppression of B4GALT2 was found to enhance CD8+ T lymphocyte populations and their functional status, thereby potentiating anti-programmed cell death protein 1 immunotherapeutic efficacy in animal studies. This phenomenon was characterized by reduced CD62L+CD8 T lymphocyte levels alongside elevated GZMB+/CD44+/CD69+CD8 T cell populations.

conclusionThe developed PTMLS system represents an effective instrument for individualized prognostic evaluation and immunotherapy stratification in both LUAD and diverse cancer populations. The identification of B4GALT2 as a previously unrecognized oncogenic factor involved in immune exclusion presents a novel therapeutic avenue for LUAD treatment and immunotherapy optimization.

Indexed as

Adenocarcinoma of LungGalactosyltransferasesLung NeoplasmsProtein Processing, Post-TranslationalAnimalsFemaleHumansMachine LearningMaleMicePrognosisGalactosyltransferasesBiomarkerImmunotherapyTumor Microenvironment

Identifiers

PMID40010763
PMCPMC11865799

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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.