Evidence map›Paper›PMID 36999020›Full record

ArticleFrontiers in immunology2023

Model for predicting immunotherapy based on M2 macrophage infiltration in TNBC.

Haoming Wu, Jikun Feng, Wenjing Zhong, Xiazi Zouxu, Zhengchong Xiong, Weiling Huang, Chao Zhang, Xi Wang, Jiarong Yi

Open access · goldFull text read
In one paragraph

Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

14 citing papers in PubMed, 13 citations in OpenAlex.

  1. 3D-bioprinted adipose-derived stem cell-secreted GAS6Journal of nanobiotechnology · 2026
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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

9 authors at 3 institutions in 1 country.

Haoming WuDepartment of Breast Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Jikun FengDepartment of Breast Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Wenjing ZhongDepartment of Breast Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Xiazi ZouxuDepartment of Breast Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Zhengchong XiongDepartment of Breast Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Weiling HuangDepartment of Breast Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Chao ZhangDepartment of Breast Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Xi WangDepartment of Breast Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Jiarong YiDepartment of Breast Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Sun Yat-sen University Cancer Center · CNState Key Laboratory of Oncology in South ChinaShantou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Compared to other types of breast cancer, triple-negative breast cancer (TNBC) does not effectively respond to hormone therapy and HER2 targeted therapy, showing a poor prognosis. There are currently a limited number of immunotherapeutic drugs available for TNBC, a field that requires additional development. Methods: Co-expressing genes with M2 macrophages were analyzed based on the infiltration of M2 macrophages in TNBC and the sequencing data in The Cancer Genome Atlas (TCGA) database. Consequently, the influence of these genes on the prognoses of TNBC patients was analyzed. GO analysis and KEGG analysis were performed for exploring potential signal pathways. Lasso regression analysis was conducted for model construction. The TNBC patients were scored by the model, and patients were divided into high- and low-risk groups. Subsequently, the accuracy of model was further verified using GEO database and patients information from the Cancer Center of Sun Yat-sen University. On this basis, we analyzed the accuracy of prognosis prediction, correlation with immune checkpoint, and immunotherapy drug sensitivity in different groups. Results: Our findings revealed that OLFML2B, MS4A7, SPARC, POSTN, THY1, and CD300C genes significantly influenced the prognosis of TNBC. Moreover, MS4A7, SPARC, and CD300C were finally determined for model construction, and the model showed good accuracy in prognosis prediction. And 50 immunotherapy drugs with therapeutic significance in different groups were screened, which were assessed possible immunotherapeutics that have potential application and demonstrated the high precision of our prognostic model for predictive analysis. Conclusion: MS4A7, SPARC, and CD300C, the three main genes used in our prognostic model, offer good precision and clinical application potential. Fifty immune medications were assessed for their ability to predict immunotherapy drugs, providing a novel approach to immunotherapy for TNBC patients and a more reliable foundation for applying drugs in subsequent treatments.

Indexed as

Triple Negative Breast NeoplasmsAntigens, SurfaceGenes, RegulatorHumansImmunotherapyMacrophagesMembrane GlycoproteinsTranscription FactorsAntigens, SurfaceCD300C protein, humanMembrane GlycoproteinsTranscription Factorsimmune infiltrationimmunotherapyM2 macrophageprognosis prediction modelTNBC

Identifiers

PMID36999020
PMCPMC10043239
OpenAlexW4324145728

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Textfull text, public
LicenceCC BY
measurements read68
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.