Evidence map›Paper›PMID 35151325›Full record

ArticleCancer cell international2022

Identification of key serum biomarkers for the diagnosis and metastatic prediction of osteosarcoma by analysis of immune cell infiltration.

Zhihao Chen, Liubing Li, Ziyuan Li, Xi Wang, Mingxiao Han, Zongshuai Gao, Min Wang, Gangfeng Hu, Xiaolu Xie, Hong Du and 2 more

Open access · goldAbstract read
In one paragraph

Article in Cancer cell international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 28% 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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Strategies to Overcome Resistance to Immune-Based Therapies in Osteosarcoma.International journal of molecular sciences · 2023
    Review
  5. Recent Advances of Circular RNAs as Biomarkers for Osteosarcoma.International journal of general medicine · 2023
    Review
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.

Zhihao Chen *Department of Orthopedics, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Liubing Li *Department of Orthopedics, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Ziyuan Li *Department of Orthopedics, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Xi WangDepartment of Clinical Laboratory, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Mingxiao HanDepartment of Clinical Laboratory, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Zongshuai GaoDepartment of Transfusion Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
Min WangDepartment of Clinical Laboratory, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Gangfeng HuDepartment of Orthopedics, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Xiaolu XieDepartment of Clinical Laboratory, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Hong DuDepartment of Clinical Laboratory, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Zonggang XieDepartment of Orthopedics, The Second Affiliated Hospital of Soochow University, Suzhou, China. 8a145@163.com.
Haifang ZhangDepartment of Clinical Laboratory, The Second Affiliated Hospital of Soochow University, Suzhou, China. haifangzhang@suda.edu.cn.ORCID http://orcid.org/0000-0001-6434-3561
Soochow University · CNShanghai Jiao Tong University · CN

Funding

National Natural Science Foundation of China 82172332
6 · The paper itself

Abstract

backgroundThe role of circular RNAs (circRNAs) and microRNAs (miRNAs) in osteosarcoma (OS) development has not been fully elucidated. Further, the contribution of the immune response to OS progression is not well defined. However, it is known that circRNAs and miRNAs can serve as biomarkers for the diagnosis, prognosis, and therapy of many cancers. Thus, the aim of this study was to identify novel key serum biomarkers for the diagnosis and metastatic prediction of OS by analysis of immune cell infiltration and associated RNA molecules.

methodsHuman OS differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) were identified by analysis of microarray data downloaded from Gene Expression Omnibus (GEO) datasets. Further, characteristic patterns of OS-infiltrating immune cells were analyzed. On this basis, we identified statistically significant transcription factors. Moreover we performed pathway enrichment analysis, constructed protein-protein interaction networks, and devised competitive endogenous RNA (ceRNA) networks. Biological targets of the ceRNA networks were evaluated and potential OS biomarkers confirmed by RT-qPCR analysis of the patients' serum.

resultsSeven differentially expressed circRNAs, 166 differentially expressed miRNAs, and 175 differentially expressed mRNAs were identified. An evaluation of cellular OS infiltration identified the highest level of infiltration by M0 macrophages, M2 macrophages, and CD8+ T cells, with M0 macrophages and CD8+ T cells as the most prominent. Significant patterns of tumor-infiltrating immune cells were identified by principal component analysis. Moreover, 185 statistically significant transcription factors were associated with OS. Further, in association with immune cell infiltration, hsa-circ-0010220, hsa-miR-326, hsa-miR-338-3p, and FAM98A were identified as potential novel biomarkers for OS diagnosis. Of these, FAM98A had the most promise as a diagnostic marker for OS and OS metastasis. Most importantly, a novel diagnostic model consisting of these four biomarkers (hsa-circ-0010220, hsa-miR-326, hsa-miR-338-3p, and FAM98A) was established with a 0.928 AUC value.

conclusionsIn summary, potential serum biomarkers for OS diagnosis and metastatic prediction were identified based on an analysis of immune cell infiltration. A novel diagnostic model consisting of these four promising serum biomarkers was established. Taken together, the results of this study provide a new perspective by which to understand immunotherapy of OS.

Indexed as

BiomarkerscircRNAImmunotherapymiRNAOsteosarcoma

Identifiers

PMID35151325
PMCPMC8841093
OpenAlexW4210970181

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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.