Evidence map›Paper›PMID 40560621›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

Genome-scale knockout simulation and clustering analysis of drug-resistant breast cancer cells reveal drug sensitization targets.

JinA Lim, Hae Deok Jung, Soo Young Park, Moonhyeon Jeon, Da Sol Kim, Ryeongeun Cho, Dohyun Han, Han Suk Ryu, Yoosik Kim, Hyun Uk Kim

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. 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

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.

  1. Article
  2. Review
  3. IntegratingFrontiers in immunology · 2026
    Review
  4. Genome-scale knockout simulation and clustering analysis of drug-resistant breast cancer cells reveal drug sensitization targets.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  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

10 authors.

JinA Lim *Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea.ORCID 0009-0003-8682-5061
Hae Deok Jung *Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea.ORCID 0000-0002-5095-369X
Soo Young ParkDepartment of Pathology, Seoul National University Hospital, Seoul 03080, Republic of Korea.
Moonhyeon JeonDepartment of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea.ORCID 0009-0006-9521-5670
Da Sol KimDepartment of Pathology, Seoul National University Hospital, Seoul 03080, Republic of Korea.
Ryeongeun ChoDepartment of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea.
Dohyun HanTransdisciplinary Department of Medicine and Advanced Technology, Seoul National University Hospital, Seoul 03080, Republic of Korea.ORCID 0000-0002-0841-1598
Han Suk RyuDepartment of Pathology, Seoul National University Hospital, Seoul 03080, Republic of Korea.
Yoosik KimDepartment of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea.ORCID 0000-0003-3064-4643
Hyun Uk KimDepartment of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea.ORCID 0000-0001-7224-642X

Funding

Electronics and Telecommunications Research Institute (ETRI) 22RB1100National Research Foundation of Korea (NRF) RS-2023-00262527National Research Foundation of Korea (NRF) RS-2024-00392438
6 · The paper itself

Abstract

Anticancer chemotherapy is an essential part of cancer treatment, but the emergence of resistance remains a major hurdle. Metabolic reprogramming is a notable phenotype associated with the acquisition of drug resistance. Here, we develop a computational framework that predicts metabolic gene targets capable of reverting the metabolic state of drug-resistant cells to that of drug-sensitive parental cells, thereby sensitizing the resistant cells. The computational framework performs single-gene knockout simulation of genome-scale metabolic models that predicts genome-wide metabolic flux distribution in drug-resistant cells, and clusters the resulting knockout flux data using uniform manifold approximation and projection, followed by

Indexed as

Antineoplastic AgentsBreast NeoplasmsDrug Resistance, NeoplasmCluster AnalysisComputer SimulationDoxorubicinFemaleGene Knockout TechniquesHumansMCF-7 CellsPaclitaxelAntineoplastic AgentsDoxorubicinPaclitaxelanticancer drug resistancedrug sensitizationgenome-scale metabolic modelmetabolic reprogrammingsingle-gene knockout simulation

Identifiers

PMID40560621
PMCPMC12232641

What OpenQuestion holds

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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.