Evidence map›Paper›PMID 33087151›Full record

ArticleCell communication and signaling : CCS2020

Kinase shRNA screening reveals that TAOK3 enhances microtubule-targeted drug resistance of breast cancer cells via the NF-κB signaling pathway.

Tsung-Ching Lai, Chih-Yeu Fang, Yi-Hua Jan, Hsiao-Ling Hsieh, Yi-Fang Yang, Chun-Yu Liu, Peter Mu-Hsin Chang, Michael Hsiao

Open access · goldAbstract read
In one paragraph

Article in Cell communication and signaling : CCS, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.6field-weighted citation impact, top 14% 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

14 citing papers in PubMed, 27 citations in OpenAlex.

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  6. The role of TAOK3 in cancer progression and development as a prognostic marker: A pan-cancer analysis study.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2024
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  14. The Diverse Roles of TAO Kinases in Health and Diseases.International journal of molecular sciences · 2020
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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 at 4 institutions in 1 country.

Tsung-Ching LaiDivision of Pulmonary Medicine, Department of Internal Medicine, Wan Fang Hospital, Taipei Medical University, Taipei, 116, Taiwan.
Chih-Yeu FangGenomics Research Center, Academia Sinica, Taipei, 115, Taiwan.
Yi-Hua JanGenomics Research Center, Academia Sinica, Taipei, 115, Taiwan.
Hsiao-Ling HsiehGenomics Research Center, Academia Sinica, Taipei, 115, Taiwan.
Yi-Fang YangDepartment of Medical Education and Research, Kaohsiung Veterans General Hospital, Kaohsiung, 81362, Taiwan.
Chun-Yu LiuDepartment of Oncology, Taipei Veterans General Hospital, Taipei, 11217, Taiwan.
Peter Mu-Hsin ChangDepartment of Oncology, Taipei Veterans General Hospital, Taipei, 11217, Taiwan. ptchang@vghtpe.gov.tw.
Michael HsiaoGenomics Research Center, Academia Sinica, Taipei, 115, Taiwan. mhsiao@gate.sinica.edu.tw.
Genomics Research Center, Academia Sinica · TWTaipei Veterans General Hospital · TWKaohsiung Veterans General Hospital · TWTaipei Medical University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChemotherapy is currently one of the most effective treatments for advanced breast cancer. Anti-microtubule agents, including taxanes, eribulin and vinca-alkaloids are one of the primary major anti-breast cancer chemotherapies; however, chemoresistance remains a problem that is difficult to solve. We aimed to discover novel candidate protein targets to combat chemoresistance in breast cancer.

methodsA lentiviral shRNA-based high-throughput screening platform was designed and developed to screen the global kinome to find new therapeutic targets in paclitaxel-resistant breast cancer cells. The phenotypes were confirmed with alternative expression in vitro and in vivo. Molecular mechanisms were investigated using global phosphoprotein arrays and expression microarrays. Global microarray analysis was performed to determine TAOK3 and genes that induced paclitaxel resistance.

resultsA serine/threonine kinase gene, TAOK3, was identified from 724 screened kinase genes. TAOK3 shRNA exhibited the most significant reduction in IC50 values in response to paclitaxel treatment. Ectopic downregulation of TAOK3 resulted in paclitaxel-resistant breast cancer cells sensitize to paclitaxel treatment in vitro and in vivo. The expression of TAOK3 also was correlated to sensitivity to two other anti-microtubule drugs, eribulin and vinorelbine. Our TAOK3-modulated microarray analysis indicated that NF-κB signaling played a major upstream regulation role. TAOK3 inhibitor, CP43, and shRNA of NF-κB both reduced the paclitaxel resistance in TAOK3 overexpressed cells. In clinical microarray databases, high TAOK3 expressed breast cancer patients had poorer prognoses after adjuvant chemotherapy.

conclusionsHere we identified TAOK3 overexpression increased anti-microtubule drug resistance through upregulation of NF-κB signaling, which reduced cell death in breast cancer. Therefore, inhibition of the interaction between TAOK3 and NF-κB signaling may have therapeutic implications for breast cancer patients treated with anti-microtubule drugs. Video abstract.

Indexed as

Drug Resistance, NeoplasmSignal TransductionAnimalsApoptosisBreast NeoplasmsBridged-Ring CompoundsCell Line, TumorCell ProliferationCyclooxygenase 2FemaleHumansKaplan-Meier EstimateMice, Inbred NODMice, SCIDMicrotubulesNF-kappa BBridged-Ring CompoundsCyclooxygenase 2NF-kappa BPaclitaxelProtein Serine-Threonine KinasesPTGS2 protein, humanRNA, Small InterferingTAOK3 protein, humantaxaneTaxoidsAnti-microtubule drug resistanceBreast cancerNF-κBTAOK3

Identifiers

PMID33087151
PMCPMC7579951
OpenAlexW3093893408

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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.