Evidence map›Paper›PMID 38097586›Full record

ArticleNature communications2023

Mapping combinatorial drug effects to DNA damage response kinase inhibitors.

Hanrui Zhang, Julian Kreis, Sven-Eric Schelhorn, Heike Dahmen, Thomas Grombacher, Michael Zühlsdorf, Frank T Zenke, Yuanfang Guan

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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

6 citing papers in PubMed.

  1. Review
  2. 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

8 authors.

Hanrui ZhangDepartment of Computational Medicine and Bioinformatics, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0001-9924-0319
Julian KreisMerck Healthcare KGaA, Darmstadt, Germany.
Sven-Eric SchelhornMerck Healthcare KGaA, Darmstadt, Germany.
Heike DahmenMerck Healthcare KGaA, Darmstadt, Germany.
Thomas GrombacherMerck Healthcare KGaA, Darmstadt, Germany.
Michael ZühlsdorfMerck Healthcare KGaA, Darmstadt, Germany.
Frank T ZenkeMerck Healthcare KGaA, Darmstadt, Germany.ORCID 0000-0002-2226-3755
Yuanfang GuanDepartment of Computational Medicine and Bioinformatics, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA. gyuanfan@umich.edu.ORCID 0000-0001-8275-2852

Funding

Machine Learning for Drug Response PredictionR35GM133346 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Yuanfang Guan · 2019 to 2026
$3.2M
NIGMS NIH HHS R35 GM133346
6 · The paper itself

Abstract

One fundamental principle that underlies various cancer treatments, such as traditional chemotherapy and radiotherapy, involves the induction of catastrophic DNA damage, leading to the apoptosis of cancer cells. In our study, we conduct a comprehensive dose-response combination screening focused on inhibitors that target key kinases involved in the DNA damage response (DDR): ATR, ATM, and DNA-PK. This screening involves 87 anti-cancer agents, including six DDR inhibitors, and encompasses 62 different cell lines spanning 12 types of tumors, resulting in a total of 17,912 combination treatment experiments. Within these combinations, we analyze the most effective and synergistic drug pairs across all tested cell lines, considering the variations among cancers originating from different tissues. Our analysis reveals inhibitors of five DDR-related pathways (DNA topoisomerase, PLK1 kinase, p53-inducible ribonucleotide reductase, PARP, and cell cycle checkpoint proteins) that exhibit strong combinatorial efficacy and synergy when used alongside ATM/ATR/DNA-PK inhibitors.

Indexed as

Cell Cycle ProteinsNeoplasmsAtaxia Telangiectasia Mutated ProteinsDNADNA DamageDNA RepairHumansAtaxia Telangiectasia Mutated ProteinsCell Cycle ProteinsDNA

Identifiers

PMID38097586
PMCPMC10721915

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.