Evidence map›Paper›PMID 36959804›Full record

ArticleFrontiers in oncology2023

Identification and verification of the temozolomide resistance feature gene DACH1 in gliomas.

Qiang Gu, Lang Li, Jiahao Yao, Fa-Yan Dong, Yifan Gan, Shuhuai Zhou, Xinyu Wang, Xue-Feng Wang

Open access · goldFull text read
In one paragraph

Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 29% 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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
  3. Dachshund Homolog 1: Unveiling Its Potential Role in Megakaryopoiesis andInternational journal of molecular sciences · 2024
    Article
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

8 authors at 1 institution in 1 country.

Qiang GuHarbin Medical University, Harbin, China.
Lang LiHarbin Medical University, Harbin, China.
Jiahao YaoHarbin Medical University, Harbin, China.
Fa-Yan DongHarbin Medical University, Harbin, China.
Yifan GanHarbin Medical University, Harbin, China.
Shuhuai ZhouHarbin Medical University, Harbin, China.
Xinyu WangHarbin Medical University, Harbin, China.
Xue-Feng WangHarbin Medical University, Harbin, China.
Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The most important chemotherapy treatment for glioma patients is temozolomide. However, the development of drug resistance severely restricts the use of temozolomide. Therefore, elucidating the mechanism of temozolomide resistance, enhancing temozolomide sensitivity, and extending patient survival are urgent tasks for researchers. Methods: Temozolomide resistance hub differential genes were identified using differential analysis and protein interaction analysis from the GEO datasets (GSE100736 and GSE113510). These genes were further studied in glioma patients treated with temozolomide in the TCGA and CGGA databases. Patients from the mRNAseq_325 dataset (CGGA) were considered as the training set to construct a risk model for predicting glioma sensitivity to temozolomide, while patients from the mRNAseq_693 dataset (CGGA) and TCGA-GBM dataset were considered as the validation set to evaluate the performance of models. PCR and western blot were performed to determine the difference in expression of the feature gene DACH1 between glioma cells and temozolomide-resistant glioma cells. The alterations in the sensitivity of tumor cells to temozolomide were also observed after DACH1 was silenced. The patients were then divided into two groups based on the expression of DACH1, and the differences in patient survival rates, molecular pathway activation, and level of immune infiltration were compared. Results: Based on four signature genes (AHR, DACH1, MGMT, and YAP1), a risk model for predicting glioma sensitivity to temozolomide was constructed, and the results of timeROC in both the training and validation sets showed that the model had good predictive performance. The expression of the signature gene DACH1 was significantly downregulated in temozolomide-resistant cells, according to the results of the PCR and western blot experiments. The sensitivity of tumor cells to temozolomide was significantly reduced after DACH1 was silenced. DACH1 probably regulates temozolomide resistance in glioblastoma through the transcriptional dysregulation in cancer and ECM. Discussion: This study constructs a risk model that can predict glioma susceptibility to temozolomide and validates the function of the feature gene DACH1, which provides a promising target for the research of temozolomide resistance.

Indexed as

drug-resistancegliomamachine learningrisk modeltemozolomide

Identifiers

PMID36959804
PMCPMC10028258
OpenAlexW4323363292

What Socratic holds

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LicenceCC BY
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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 Socratic graph.