Evidence map›Paper›PMID 33070512›Full record

ArticleZhongguo fei ai za zhi = Chinese journal of lung cancer2020

[Prognostic Analysis of NSCLC Based on the Tumor-associated Macrophages, Tumor Neo-vessels and PD-L1 Expression in Tumor Microenvironment].

Qingqing Hang, Hangjie Ying, Guoping Cheng, Shifeng Yang, Jianan Jin, Yamei Chen, Qixun Chen, Youhua Jiang, Qiang Zhao, Min Fang and 2 more

Open access · greenAbstract read
In one paragraph

Article in Zhongguo fei ai za zhi = Chinese journal of lung cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 51% 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

2 citing papers in PubMed, 2 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

12 authors at 2 institutions in 1 country.

Qingqing HangThe Second Clinical Medical College Zhejiang Chinese Medical University, Hangzhou 310053, China.
Hangjie YingZhejiang Key Laboratory of Radiation Oncology, Department of Thoracic Radiotherapy, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310022, China.
Guoping ChengDepartment of Pathology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310022, China.
Shifeng YangDepartment of Pathology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310022, China.
Jianan JinThe Second Clinical Medical College Zhejiang Chinese Medical University, Hangzhou 310053, China.
Yamei ChenZhejiang Key Laboratory of Radiation Oncology, Department of Thoracic Radiotherapy, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310022, China.
Qixun ChenDepartment of Thoracic Surgery, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310022, China.
Youhua JiangDepartment of Thoracic Surgery, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310022, China.
Qiang ZhaoDepartment of Thoracic Surgery, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310022, China.
Min FangZhejiang Key Laboratory of Radiation Oncology, Department of Thoracic Radiotherapy, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310022, China.
Ming ChenZhejiang Key Laboratory of Radiation Oncology, Department of Thoracic Radiotherapy, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310022, China.
Xiaojing LaiZhejiang Key Laboratory of Radiation Oncology, Department of Thoracic Radiotherapy, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310022, China.
Zhejiang Cancer Hospital · CNZhejiang Chinese Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTumor microenvironment is a complex and dynamic community, which plays a crucial role in tumor progression via the co-evolution of cancer cells and tumor stroma. Among them, tumor-associated macrophages (TAMs) and tumor neo-vessels are two key components in the tumor microenvironment during cancer invasion. In addition, programmed cell death ligand 1/programmed cell death ligand 1 (PD-1/PD-L1) also plays an important role in tumorigenesis and development, and the clinical strategies to block PD-1/PD-L1 pathway could have great benefits for cancer patients. This study was aimed at analyzing the quantitative expression and prognostic significance of TAMs, tumor neo-vessels and PD-L1 in tumor microenvironment and exploring the relations between the expression of above components with the patients' prognosis of non-small cell lung cancer (NSCLC).

methodsClinico-pathological data and surgical specimens of 92 patients with NSCLC were collected, and immunohistochemistry was used to stain the expression of TAMs, tumor neo-vessels and PD-L1 on tumor tissue and peri-tumor tissues. The inverted microscopy was used to take pictures and Image-pro Plus 6.0 software was used for quantitative analysis. The clinicopathological characteristics and overall survival (OS) were analyzed.

resultsThe median OS of 92 NSCLC cases was 22.5 month. The expression of TAMs, tumor neo-vessels and PD-L1 in tumor tissue and peri-tumor tissues were not statistically significant (P>0.05). According to the cutoff of above key three components in tumor microenvironment, all the cases could be classified into high, middle and low expression groups. The survival analysis demonstrated that the OS in high expression group of TAMs (P=0.016) and PD-L1 (P=0.002) was shorter than the other two groups, respectively, with statistical significance. The OS in high tumor neo vessels group was shorter than the other two groups. However, there was no statistical significance between these three group (P=0.626). Combined with above the three components, all the cases could be classified into low, middle and high density groups. The survival analysis demonstrated that the median OS of combined high density group was shorter than the other two groups (P=0.001). Multivariate analysis by Cox regression indicated that pathological type, TAMs and PD-L1 expression were the independent prognostic factors.

conclusionsThe key components of TAMs and PD-L1 in tumor microenvironment are closely related to the prognosis of NSCLC patients.

Indexed as

AdultAgedAntigens, CDAntigens, Differentiation, MyelomonocyticB7-H1 AntigenCarcinoma, Non-Small-Cell LungCD68 MoleculeEndoglinFemaleHumansLung NeoplasmsMaleMiddle AgedPrognosisTumor-Associated MacrophagesTumor MicroenvironmentAntigens, CDAntigens, Differentiation, MyelomonocyticB7-H1 AntigenCD68 antigen, humanCD68 MoleculeEndoglinLung neoplasmsProgrammed cell death ligand 1Tumor-associated macrophagesTumor microenvironmentTumor neo-vessels

Identifiers

PMID33070512
PMCPMC7583870
OpenAlexW3092679264

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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.