Evidence map›Paper›PMID 34622176›Full record

ArticleiScience2021

Discovering a qualitative transcriptional signature of homologous recombination defectiveness for prostate cancer.

Yawei Li, Zhangxiang Zhao, Liqiang Ai, Yuquan Wang, Kaidong Liu, Bo Chen, Tingting Chen, Shuping Zhuang, Huanhuan Xu, Min Zou and 2 more

Abstract read
In one paragraph

Article in iScience, 2021. 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
–field-weighted citation impact
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

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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.

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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

12 authors.

Yawei LiDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Zhangxiang ZhaoDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Liqiang AiDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Yuquan WangDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Kaidong LiuDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Bo ChenDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Tingting ChenDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Shuping ZhuangDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Huanhuan XuDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Min ZouDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Yunyan GuDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Xia LiDepartment of Bioinformatics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The discovery of homologous recombination deficiency (HRD) biomarkers in prostate cancer is important for patients who will benefit from poly ADP-ribose polymerase inhibitor (PARPi). Here, we developed a transcriptional homologous recombination defectiveness (HRDness) signature, comprising 16 gene pairs (16-GPS), for prostate cancer by a relative expression ordering (REO)-based discovery procedure. Subsequently, two newly subtypes classified by 16-GPS showed a higher significance level in various clinicopathological and HRD features than subtypes obtained by other methods, such as HRDetect. HRDness subtype also displayed more aggressive features and higher genomics scores than non-HRDness in three independent datasets. HRDness prostate cancer cells were more sensitive to PARPi than non-HRDness. Moreover, the HRDness samples showed distinct multi-omics characteristics related to homologous recombination repair function loss. Overall, the newly proposed qualitative signature can robustly determine the HRD status for prostate cancer at the personalized level, and especially be an auxiliary tool for PARPi treatment strategy.

Indexed as

CancerGenomicsTranscriptomics

Identifiers

PMID34622176
PMCPMC8482486

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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.