Evidence map›Paper›PMID 36172179›Full record

ArticleFrontiers in pharmacology2022

Establishment, immunological analysis, and drug prediction of a prognostic signature of ovarian cancer related to histone acetylation.

Yujie Fang, Jing Zhao, Xu Guo, Yunfeng Dai, Hao Zhang, Fanxin Yin, Xiaoxu Zhang, Chenxi Sun, Zequan Han, Hecheng Wang and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pharmacology, 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
0.9field-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

5 citing papers in PubMed, 10 citations in OpenAlex.

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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

11 authors at 3 institutions in 1 country.

Yujie FangSchool of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China.
Jing ZhaoSchool of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China.
Xu GuoSchool of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China.
Yunfeng DaiDepartment of Radiotherapy, Yingkou Central Hospital, Yingkou, China.
Hao ZhangSchool of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China.
Fanxin YinSchool of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China.
Xiaoxu ZhangSchool of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China.
Chenxi SunSchool of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China.
Zequan HanDepartment of Pathology, Yingkou Fangda Hospital, Yingkou, China.
Hecheng WangSchool of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China.
Yanshuo HanSchool of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China.
Dalian University · CNDalian University of Technology · CNYingkou Institute of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, epigenetic modifications have been increasingly regarded as an important hallmark of cancer. Histone acetylation, as an important part of epigenetic modification, plays a key role in the progress, treatment, and prognosis of many cancers. In this study, based on the TCGA database, we performed LASSO regression and the Cox algorithm to establish a prognostic signature of ovarian cancer associated with histone acetylation modulator genes and verified it externally in the GEO database. Subsequently, we performed an immunological bioinformatics analysis of the model from multiple perspectives using the CIBERSORT algorithm, ESTIMATE algorithm, and TIDE algorithm to verify the accuracy of the model. Based on the prognostic model, we divided ovarian cancer patients into high-risk and low-risk groups, and assessed survival and the efficacy of accepting immunosuppressive therapy. In addition, based on the analysis of characteristics of the model, we also screened targeted drugs for high-risk patients and predicted potential drugs that inhibit platinum resistance through the connectivity map method. We ultimately constructed a histone acetylation modulator-related signature containing 10 histone acetylation modulators, among which HDAC1, HDAC10, and KAT7 can act as independent prognostic factors for ovarian cancer and are related to poor prognosis. In the analysis of the tumor microenvironment, the proportion of the B-infiltrating cells and the macrophages was significantly different between the high- and low-risk groups. Also, the samples with high-risk scores had higher tumor purity and lower immune scores. In terms of treatment, patients in the high-risk group who received immunotherapy had a higher likelihood of immune escape or rejection and were less likely to respond to platinum/paclitaxel therapy. Finally, we screened 20 potential drugs that could target the model for reference.

Indexed as

histone acetylationimmune therapyovarian cancerprognostic markerstargeted therapy

Identifiers

PMID36172179
PMCPMC9510621
OpenAlexW4296528098

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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.