Evidence map›Paper›PMID 29255247›Full record

ArticleOncogene2018

GNA13 expression promotes drug resistance and tumor-initiating phenotypes in squamous cell cancers.

Suhail Ahmed Kabeer Rasheed, Hui Sun Leong, Manikandan Lakshmanan, Anandhkumar Raju, Dhivya Dadlani, Fui-Teen Chong, Nicholas B Shannon, Ravisankar Rajarethinam, Thakshayeni Skanthakumar, Ern Yu Tan and 8 more

Open access · hybridAbstract read
In one paragraph

Article in Oncogene, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
1.2field-weighted citation impact, top 23% 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

31 citing papers in PubMed, 60 citations in OpenAlex.

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  17. GαFrontiers in cell and developmental biology · 2022
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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

18 authors at 8 institutions in 3 countries.

Suhail Ahmed Kabeer RasheedProgramme in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore, Singapore.ORCID 0000-0002-7674-7560
Hui Sun LeongCancer Therapeutics Research Laboratory, National Cancer Centre, Singapore, Singapore.
Manikandan LakshmananMouse Models for Human Cancer Unit, Institute of Molecular and Cell Biology, Singapore, Singapore.
Anandhkumar RajuMouse Models for Human Cancer Unit, Institute of Molecular and Cell Biology, Singapore, Singapore.
Dhivya DadlaniProgramme in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore, Singapore.
Fui-Teen ChongCancer Therapeutics Research Laboratory, National Cancer Centre, Singapore, Singapore.
Nicholas B ShannonDepartment of Surgical Oncology, National Cancer Centre, Singapore, Singapore.
Ravisankar RajarethinamAdvanced Molecular Pathology Laboratory, Singapore, Singapore.
Thakshayeni SkanthakumarDepartment of Surgical Oncology, National Cancer Centre, Singapore, Singapore.
Ern Yu TanDepartment of General Surgery, Tan Tock Seng Hospital, Singapore, Singapore.
Jacqueline Siok Gek HwangDepartment of Pathology, Singapore General Hospital, Singapore, Singapore.
Kok Hing LimDepartment of Pathology, Singapore General Hospital, Singapore, Singapore.
Daniel Shao-Weng TanCancer Therapeutics Research Laboratory, National Cancer Centre, Singapore, Singapore.
Paolo CeppiIZKF Junior Research Group, Friedrich-Alexander-Universitaet Erlangen-Nuernberg, Erlangen, Germany.
Mei WangProgramme in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore, Singapore.
Vinay TergaonkarMouse Models for Human Cancer Unit, Institute of Molecular and Cell Biology, Singapore, Singapore.
Patrick J CaseyProgramme in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore, Singapore. patrick.casey@duke-nus.edu.sg.
N Gopalakrishna IyerProgramme in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore, Singapore. gopaliyer@nccs.com.sg.
National Cancer Centre Singapore · SGDuke-NUS Medical School · SGInstitute of Molecular and Cell Biology · SGSingapore General Hospital · SGAdvanced Digital Sciences Center · SGDuke University · USFriedrich-Alexander-Universität Erlangen-Nürnberg · DETan Tock Seng Hospital · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Treatment failure in solid tumors occurs due to the survival of specific subpopulations of cells that possess tumor-initiating (TIC) phenotypes. Studies have implicated G protein-coupled-receptors (GPCRs) in cancer progression and the acquisition of TIC phenotypes. Many of the implicated GPCRs signal through the G protein GNA13. In this study, we demonstrate that GNA13 is upregulated in many solid tumors and impacts survival and metastases in patients. GNA13 levels modulate drug resistance and TIC-like phenotypes in patient-derived head and neck squamous cell carcinoma (HNSCC) cells in vitro and in vivo. Blockade of GNA13 expression, or of select downstream pathways, using small-molecule inhibitors abrogates GNA13-induced TIC phenotypes, rendering cells vulnerable to standard-of-care cytotoxic therapies. Taken together, these data indicate that GNA13 expression is a potential prognostic biomarker for tumor progression, and that interfering with GNA13-induced signaling provides a novel strategy to block TICs and drug resistance in HNSCCs.

Indexed as

AnimalsAntineoplastic AgentsBiomarkers, TumorCell ProliferationCell Transformation, NeoplasticDrug Resistance, NeoplasmGene Expression Regulation, NeoplasticGTP-Binding Protein alpha SubunitsGTP-Binding Protein alpha Subunits, G12-G13HumansMiceMice, Inbred NODMice, SCIDPhenotypeSignal TransductionSquamous Cell Carcinoma of Head and NeckAntineoplastic AgentsBiomarkers, TumorGNA13 protein, humanGTP-Binding Protein alpha SubunitsGTP-Binding Protein alpha Subunits, G12-G13

Identifiers

PMID29255247
PMCPMC6168473
OpenAlexW2774210001

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.