Evidence map›Paper›PMID 42135620›Full record

ArticleBiological procedures online2026

Identification and validation of serum SLIT1 as a biomarker for predicting anti-PD-1/PD-L1 resistance in non-small cell lung cancer.

Huisi Qiu, Cong Peng, Ziao Gao, Huafeng Luo, Ying Wei, Yuanfeng Huang, Danyang Chen, Ying Song, Kai Luo, Hao Liu and 2 more

Abstract read
In one paragraph

Article in Biological procedures online, 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

12 authors.

Huisi Qiu *Affiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Rd, Guangzhou, Guangdong, 510095, China.
Cong Peng *Affiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Rd, Guangzhou, Guangdong, 510095, China.
Ziao GaoAffiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Rd, Guangzhou, Guangdong, 510095, China.
Huafeng LuoAffiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Rd, Guangzhou, Guangdong, 510095, China.
Ying WeiAffiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Rd, Guangzhou, Guangdong, 510095, China.
Yuanfeng HuangAffiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Rd, Guangzhou, Guangdong, 510095, China.
Danyang ChenAffiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Rd, Guangzhou, Guangdong, 510095, China.
Ying SongAffiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Rd, Guangzhou, Guangdong, 510095, China.
Kai LuoAffiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Rd, Guangzhou, Guangdong, 510095, China.
Hao LiuAffiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Rd, Guangzhou, Guangdong, 510095, China. liuhao@gzhmu.edu.cn.
Xin LinAffiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Rd, Guangzhou, Guangdong, 510095, China. 1318596034@qq.com.
Qian WangAffiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Rd, Guangzhou, Guangdong, 510095, China. 13798040957@163.com.

Funding

Guangdong Medical Research Foundation A2024277Natural Science Foundation of Guangdong Province 2023A1515220255
6 · The paper itself

Abstract

backgroundNon-small cell lung cancer (NSCLC), the predominant subtype of lung cancer, contributes greatly to cancer-related mortality worldwide. Although inhibitors of programmed cell death protein 1 (PD-1) and its ligand PD-L1 have markedly improved patient outcomes, treatment resistance remains a substantial clinical challenge, underscoring the need for more effective predictive biomarkers. This study aimed to identify novel biomarkers for predicting treatment efficacy and clinical prognosis by systematically analyzing serum protein profiles of patients with divergent immunotherapy responses using four-dimensional data-independent acquisition (4D-DIA) proteomics integrated with the DB4000 platform.

resultsA total of 49 differentially expressed proteins were identified between treatment-resistant and treatment-sensitive patients, with Slit Guidance Ligand 1 (SLIT1) exhibiting the most pronounced downregulation (log₂[fold-change] ≈ - 2.29, P = 0.0419). In an independent validation cohort, enzyme-linked immunosorbent assay indicated that SLIT1 expression was significantly higher in resistant patients than in sensitive patients (P < 0.0001). Furthermore, elevated SLIT1 expression was independently associated with shorter progression-free survival. A prognostic model integrating SLIT1 with other clinical variables demonstrated excellent discriminative performance (area under the curve = 0.964, 95% confidence interval: 0.929-0.998). Single-cell transcriptomic analysis further revealed a significant enrichment of SLIT1 expression within myeloid-lineage cells, particularly in M2-polarized macrophages (P = 0.0396), suggesting its involvement in modulating an immunosuppressive tumor microenvironment that may underlie treatment resistance.

conclusionsBy employing an integrated multiomics framework, this study validated serum SLIT1 as a pivotal biomarker for predicting resistance to PD-1/PD-L1 inhibitors in patients with NSCLC and concurrently elucidated its correlation with an immunosuppressive tumor microenvironment. These findings not only offer a potential predictive tool for clinical application but also lay the groundwork for future mechanistic investigations and the development of optimized therapeutic strategies.

Indexed as

BiomarkerNon-small cell lung cancerPD-1/PD-L1 immunotherapyProteomics

Identifiers

PMID42135620
PMCPMC13343707

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.