Evidence map›Paper›PMID 35885996›Full record

ArticleGenes2022

DNA Methylation-Specific Analysis of G Protein-Coupled Receptor-Related Genes in Pan-Cancer.

Mengyan Zhang, Jiyun Zhao, Huili Dong, Wenhui Xue, Jie Xing, Ting Liu, Xiuwen Yu, Yue Gu, Baoqing Sun, Haibo Lu and 1 more

Open access · goldAbstract read
In one paragraph

Article in Genes, 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
2.3field-weighted citation impact, top 11% 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, 6 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
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  5. 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

11 authors at 4 institutions in 1 country.

Mengyan ZhangComputational Biology Research Center, School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
Jiyun ZhaoComputational Biology Research Center, School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
Huili DongComputational Biology Research Center, School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
Wenhui XueComputational Biology Research Center, School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
Jie XingComputational Biology Research Center, School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
Ting LiuCollege of pathology, Qiqihar Medical University, Qiqihar 161042, China.
Xiuwen YuCollege of pathology, Qiqihar Medical University, Qiqihar 161042, China.
Yue GuComputational Biology Research Center, School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
Baoqing SunState Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou 510089, China.
Haibo LuDepartment of Gastrointestinal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin 150000, China.
Yan ZhangComputational Biology Research Center, School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
Harbin Institute of Technology · CNQiqihar Medical University · CNState Key Laboratory of Respiratory Disease · CNHarbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumor heterogeneity presents challenges for personalized diagnosis and treatment of cancer. The identification method of cancer-specific biomarkers has important applications for the diagnosis and treatment of cancer types. In this study, we analyzed the pan-cancer DNA methylation data from TCGA and GEO, and proposed a computational method to quantify the degree of specificity based on the level of DNA methylation of G protein-coupled receptor-related genes (GPCRs-related genes) and to identify specific GPCRs DNA methylation biomarkers (GRSDMs) in pan-cancer. Then, a ridge regression-based method was used to discover potential drugs through predicting the drug sensitivities of cancer samples. Finally, we predicted and verified 8 GRSDMs in adrenocortical carcinoma (ACC), rectum adenocarcinoma (READ), uveal Melanoma (UVM), thyroid carcinoma (THCA), and predicted 4 GRSDMs (F2RL3, DGKB, GRK5, PIK3R6) which were sensitive to 12 potential drugs. Our research provided a novel approach for the personalized diagnosis of cancer and informed individualized treatment decisions.

Indexed as

MelanomaThyroid NeoplasmsBiomarkers, TumorDNA MethylationGenetic MarkersHumansReceptors, G-Protein-CoupledBiomarkers, TumorGenetic MarkersReceptors, G-Protein-CoupledbiomarkerDNA methylationdrug sensitivityG protein-coupled receptor

Identifiers

PMID35885996
PMCPMC9320183
OpenAlexW4284885828

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.