Evidence map›Paper›PMID 37672187›Full record

ArticleBiochemical genetics2024

Identifying Genetic Signatures Associated with Oncogene-Induced Replication Stress in Osteosarcoma and Screening for Potential Targeted Drugs.

Meng Gao, Weibo Liu, Teng Li, ZeLong Song, XiangYu Wang, XueSong Zhang

Abstract read
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In one paragraph

Article in Biochemical genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.6field-weighted citation impact, top 16% 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

8 citing papers in PubMed, 6 citations in OpenAlex.

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  6. Review
  7. [The study on effect of EIF3B in laryngeal carcinoma].Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery · 2025
    Article
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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

6 authors at 2 institutions in 1 country.

Meng GaoSchool of Medicine, Nankai University, Tianjin, China.
Weibo LiuDepartment of Orthopaedics, The Fourth Medical Centre, Chinese PLA General Hospital, Haidian District, 51 Fucheng Road, Beijing, 100048, China.
Teng LiDepartment of Orthopaedics, The Fourth Medical Centre, Chinese PLA General Hospital, Haidian District, 51 Fucheng Road, Beijing, 100048, China.
ZeLong SongSchool of Medicine, Nankai University, Tianjin, China.
XiangYu Wang *Department of Pain Medicine, First Medical Center, PLA General Hospital, Beijing, 100000, China. wxy176@163.com.
XueSong Zhang *School of Medicine, Nankai University, Tianjin, China. zhangxs2019@yeah.net.
Chinese PLA General Hospital · CNNankai University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Osteosarcoma is the most common type of primary malignant bone tumor. Due to the lack of selectivity and sensitivity of chemotherapy drugs to tumor cells, coupled with the use of large doses, chemotherapy drugs often have systemic toxicity. The use of modern sequencing technology to screen tumor markers in a large number of tumor samples is a common method for screening highly specific and selective anti-tumor drugs. This study aims to identify potential biomarkers using the latest reported gene expression signatures of oncogene-induced replication stress (ORS) in aggressive cancers, and potential anti-osteosarcoma drugs were screened in different drug databases. In this study, we obtained 89 osteosarcoma-related samples in the TARGET database, all of which included survival information. According to the median expression of each of six reported ORS gene markers (NAT10/DDX27/ZNF48/C8ORF33/MOCS3/MPP6), we divided 89 osteosarcoma gene expression datasets into a high expression group and a low expression group and then performed a differentially expressed gene (DEG) analysis. The coexisting genes of 6 groups of DEGs were used as replication stress-related genes (RSGs) of osteosarcoma. Then, key RSGs were screened using LASSO regression, a Cox risk proportional regression prognostic model and a tenfold cross-validation test. GSE21257 datasets collected from the Gene Expression Omnibus (GEO) database were used to verify the prognostic model. The final key RSGs selected were used in the L1000PWD and DGIdb databases to mine potential drugs. After further validation by the prognostic model, we identified seven genes associated with ORS in osteosarcoma as key RSGs, including transcription factor 7 like 2 (TCF7L2), solute carrier family 27 member 4 (SLC27A4), proprotein convertase subtilisin/kexin type 5 (PCSK5), nucleolar protein 6 (NOL6), coiled-coil-coil-coil-coil-helix domain containing 4 (CHCHD4), eukaryotic translation initiation factor 3 subunit B (EIF3B), and synthesis of cytochrome C oxidase 1 (SCO1). Then, we screened the seven key RSGs in two drug databases and found six potential anti-osteosarcoma drugs (D GIdb database: repaglinide, tacrolimus, sirolimus, cyclosporine, and hydrochlorothiazide; L1000PWD database: the small molecule VU-0365117-1). Seven RSGs (TCF7L2, SLC27A4, PCSK5, NOL6, CHCHD4, EIF3B, and SCO1) may be associated with the ORS gene signatures in osteosarcoma. Repaglinide, tacrolimus, sirolimus, cyclosporine, hydrochlorothiazide and the small molecule VU-0365117-1 are potential therapeutic drugs for osteosarcoma.

Indexed as

Bone NeoplasmsOncogenesOsteosarcomaAntineoplastic AgentsBiomarkers, TumorGene Expression Regulation, NeoplasticHumansTranscriptomeAntineoplastic AgentsBiomarkers, TumorBioinformatics analysisBiomarker discoveryDrugOncogeneOsteosarcomaPrecision medicineReplication stress

Identifiers

PMID37672187
OpenAlexW4386466516

What OpenQuestion holds

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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.