Evidence map›Paper›PMID 42425715›Full record

ArticleJournal for immunotherapy of cancer2026

Plasma proteomics predicts pathological complete response and reveals LIF as a potential mediator of resistance to neoadjuvant immunochemotherapy in resectable NSCLC.

Shoucheng Feng, Ziqing Feng, Songzuo Xie, Yuheng Zhou, Weizhen Sun, Nengqi Lin, Zhichao Lin, Qinglin Wang, Zerui Zhao, Yaobin Lin and 1 more

Abstract read
In one paragraph

Article in Journal for immunotherapy of cancer, 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.

Shoucheng Feng *Department of Thoracic Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China.ORCID http://orcid.org/0000-0002-9325-2236
Ziqing Feng *Department of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China.
Songzuo Xie *Department of Nuclear Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China.
Yuheng ZhouDepartment of Thoracic Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China.ORCID http://orcid.org/0009-0005-9324-4526
Weizhen SunDepartment of Thoracic Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China.
Nengqi LinDepartment of Thoracic Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China.
Zhichao LinDepartment of Thoracic Surgery, Jiangmen Central Hospital, Jiangmen, China.
Qinglin WangDepartment of Thoracic Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China.
Zerui ZhaoDepartment of Thoracic Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China longhao@sysucc.org.cn linyaob@sysucc.org.cn zhaozr@sysucc.org.cn.
Yaobin LinDepartment of Thoracic Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China longhao@sysucc.org.cn linyaob@sysucc.org.cn zhaozr@sysucc.org.cn.
Hao LongDepartment of Thoracic Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China longhao@sysucc.org.cn linyaob@sysucc.org.cn zhaozr@sysucc.org.cn.ORCID http://orcid.org/0000-0001-5623-9799

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNeoadjuvant immunochemotherapy (nICT) is increasingly used for resectable non-small cell lung cancer (NSCLC), yet a substantial proportion of patients fail to achieve pathological complete response (pCR). Clinically scalable, minimally invasive biomarkers that predict response and point to actionable resistance mechanisms remain needed.

methodsPretreatment plasma samples collected prior to the first dose were profiled using the Olink proximity extension assay in a Sun Yat-sen University Cancer Center cohort (n=86), randomly split into a training set (n=65) and an internal validation set (n=21). Differentially abundant proteins associated with pCR were identified, and predictive models were developed using logistic regression, random forest, and extreme gradient boosting (XGBoost), followed by internal validation and independent external validation in the Jiangmen Central Hospital cohort (n=46). Survival associations were evaluated by Cox regression. Mechanistic analyses integrated tumor immunohistochemistry/multiplex immunofluorescence, bulk RNA sequencing with immune deconvolution, and functional validation in subcutaneous and orthotopic murine lung cancer models with pharmacologic leukemia inhibitory factor (LIF) blockade.

resultsFour candidate proteins (LIF, CXCL1, CX3CL1, and NT-3) showed modest single-marker discrimination for pCR (area under the curve (AUC), 0.611-0.673). Multiprotein models improved prediction, with XGBoost achieving the highest performance (training AUC=0.95; internal validation AUC=0.845 (95% CI 0.65 to 1.00); external validation AUC=0.801 (95% CI, 0.57 to 0.93)). SHapley Additive exPlanations analysis identified LIF as the dominant feature negatively associated with pCR probability. Elevated baseline plasma LIF was associated with inferior overall survival (HR=13.003; 95% CI 1.456 to 116.135; p=0.0217) and progression-free survival (HR=3.75; 95% CI 1.362 to 10.327; p=0.0105) after nICT. High LIF tumors exhibited reduced CD8

conclusionsBaseline plasma proteomics shows promise for predicting pCR to nICT in resectable NSCLC and nominates LIF as a predictive, prognostic, and therapeutic candidate mediator of resistance. These findings warrant prospective validation and further investigation of LIF-targeted combination strategies in the neoadjuvant setting.

Indexed as

Biomarkers, TumorCarcinoma, Non-Small-Cell LungImmunotherapyLeukemia Inhibitory FactorLung NeoplasmsNeoadjuvant TherapyProteomicsAnimalsDrug Resistance, NeoplasmFemaleHumansMaleMiceMiddle AgedPathologic Complete ResponseBiomarkers, TumorLeukemia Inhibitory FactorLIF protein, humanBiomarkerImmune Checkpoint InhibitorImmunotherapyLung Cancer

Identifiers

PMID42425715
PMCPMC13358280

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.