Evidence map›Paper›PMID 35529784›Full record

ArticleTranslational lung cancer research2022

Macrophages-based immune-related risk score model for relapse prediction in stage I-III non-small cell lung cancer assessed by multiplex immunofluorescence.

Xiang-Rong Wu, Hao-Xin Peng, Miao He, Ran Zhong, Jun Liu, Yao-Kai Wen, Cai-Chen Li, Jian-Fu Li, Shan Xiong, Tao Yu and 5 more

Open access · diamondAbstract read
In one paragraph

Article in Translational lung cancer research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
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

11 citing papers in PubMed, 17 citations in OpenAlex.

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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

15 authors at 6 institutions in 1 country.

Xiang-Rong Wu *Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Hao-Xin Peng *Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Miao He *Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Ran ZhongDepartment of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Jun LiuDepartment of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Yao-Kai WenSchool of Medicine, Tongji University, Shanghai, China.
Cai-Chen LiDepartment of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Jian-Fu LiDepartment of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Shan XiongDepartment of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Tao YuGenecast Biotechnology Co., Ltd., Wuxi, China.
Hong-Bo ZhengGenecast Biotechnology Co., Ltd., Wuxi, China.
Yan-Hui ChenGenecast Biotechnology Co., Ltd., Wuxi, China.
Jian-Xing HeDepartment of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Wen-Hua LiangDepartment of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Xiu-Yu CaiDepartment of General Internal Medicine, Sun Yat-sen University Cancer Centre, State Key Laboratory of Oncology in South China, Collaborative Innovation Centre for Cancer Medicine, Guangzhou, China.
First Affiliated Hospital of Guangzhou Medical University · CNGenecast (China) · CNGuangzhou Medical University · CNState Key Laboratory of Respiratory Disease · CNSun Yat-sen University Cancer Center · CNTongji University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Macrophages are critical players in regulating innate and adaptive immunity in the tumor microenvironment (TME). The prognostic value of macrophages and their heterogeneous phenotypes in non-small cell lung cancer (NSCLC) is still uncertain. Methods: Surgically-resected samples of 681 NSCLC cases were stained by multiplex immunofluorescence to examine macrophage phenotypes as well as the expression levels of program death-ligand 1 (PD-L1) on them in both tumor nest and tumor stroma, including pan-macrophage (CD68+), M1 (CD68+CD163-), and M2 macrophages (CD68+CD163+). Various other immune cell markers, including CD4, CD8, CD20, CD38, CD66B, FOXP3, and CD133, were also evaluated. Machine learning algorithm by Random Forest (RF) model was utilized to screen the robust prognostic markers and construct the CD68-based immune-related risk score (IRRS) for predicting disease-free survival (DFS). Results: The expression levels of CD68 were moderately correlated with the levels of PD-L1 (P<0.001), CD133 (P<0.001), and CD8 (P<0.001). Higher levels of CD68 (OR 1.03, 95% CI: 1.01-1.05, P<0.001) as well as M1 macrophage (OR 1.04, 95% CI: 1.01-1.06, P<0.001) indicated shorter DFS. Despite without statiscial significance, intratumoral M2 macrophage (OR 1.05, 95% CI: 0.99-1.10, P=0.081) was also associated with worse DFS. IRRS incorporating three intratumoral CD68-related markers and four intrastromal markers was constructed and validated to predict recurrence (high-risk group Conclusions: Our study suggested close interactions between CD68 and other immune markers in TME, demonstrating the prognostic value of CD68 in relapse prediction in resectable NSCLC.

Indexed as

immune-related risk scoreNon-small cell lung cancer (NSCLC)random forest algorithmtumor-associated macrophagestumor microenvironment

Identifiers

PMID35529784
PMCPMC9073743
OpenAlexW4229457950

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.