Evidence map›Paper›PMID 37090691›Full record

ArticleFrontiers in immunology2023

A novel molecular signature for predicting prognosis and immunotherapy response in osteosarcoma based on tumor-infiltrating cell marker genes.

Haijun Tang, Shangyu Liu, Xiaoting Luo, Yu Sun, Xiangde Li, Kai Luo, Shijie Liao, Feicui Li, Jiming Liang, Xinli Zhan and 3 more

Open access · goldAbstract 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 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

12 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
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  8. Article
  9. Role of Immunotherapy in Sarcomas.International journal of molecular sciences · 2024
    Review
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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

13 authors at 2 institutions in 1 country.

Haijun TangDepartment of Spine and Osteopathic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Shangyu LiuDepartment of Spine and Osteopathic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Xiaoting LuoDepartment of Pharmacy, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Yu SunDepartment of Spine and Osteopathic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Xiangde LiDepartment of Radiotherapy, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Kai LuoDepartment of Spine and Osteopathic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Shijie LiaoDepartment of Orthopedics, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Feicui LiDepartment of Spine and Osteopathic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Jiming LiangDepartment of Spine and Osteopathic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Xinli ZhanDepartment of Spine and Osteopathic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Qingjun WeiDepartment of Orthopedics, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Yun LiuDepartment of Spine and Osteopathic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Maolin HeDepartment of Spine and Osteopathic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Guangxi Medical University · CNFirst Affiliated Hospital of GuangXi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Tumor infiltrating lymphocytes (TILs), the main component in the tumor microenvironment, play a critical role in the antitumor immune response. Few studies have developed a prognostic model based on TILs in osteosarcoma. Methods: ScRNA-seq data was obtained from our previous research and bulk RNA transcriptome data was from TARGET database. WGCNA was used to obtain the immune-related gene modules. Subsequently, we applied LASSO regression analysis and SVM algorithm to construct a prognostic model based on TILs marker genes. What's more, the prognostic model was verified by external datasets and experiment Results: Eleven cell clusters and 2044 TILs marker genes were identified. WGCNA results showed that 545 TILs marker genes were the most strongly related with immune. Subsequently, a risk model including 5 genes was developed. We found that the survival rate was higher in the low-risk group and the risk model could be used as an independent prognostic factor. Meanwhile, high-risk patients had a lower abundance of immune cell infiltration and many immune checkpoint genes were highly expressed in the low-risk group. The prognostic model was also demonstrated to be a good predictive capacity in external datasets. The result of RT-qPCR indicated that these 5 genes have differential expression which accorded with the predicting outcomes. Conclusions: This study developed a new molecular signature based on TILs marker genes, which is very effective in predicting OS prognosis and immunotherapy response.

Indexed as

Bone NeoplasmsOsteosarcomaAlgorithmsBiomarkers, TumorHumansImmunotherapyPrognosisTumor MicroenvironmentBiomarkers, Tumorimmunologyosteosarcomarisk scoresingle-cell RNA sequencingtumor infiltrating lymphocytes

Identifiers

PMID37090691
PMCPMC10117669
OpenAlexW4362672730

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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.