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Record W2742567780 · doi:10.1007/s13402-017-0343-7

Increased EGFR expression induced by a novel oncogene, CUG2, confers resistance to doxorubicin through Stat1-HDAC4 signaling

2017· article· en· W2742567780 on OpenAlexaff
Sirichat Kaowinn, Seung Won Jun, Chang Seok Kim, Dong‐Myeong Shin, Yoon‐Hwae Hwang, Kyujung Kim, Bo Sung Shin, Chutima Kaewpiboon, Hyeon Hee Jeong, Sang Seok Koh, Oliver H. Krämer, Randal N. Johnston, Young‐Hwa Chung

Bibliographic record

VenueCellular Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsUniversity of Calgary
FundersMinistry of Science, ICT and Future PlanningNational Research Foundation
KeywordsGene silencingA549 cellCancer researchMAPK/ERK pathwayProtein kinase BTransfectionApoptosisDownregulation and upregulationOncogeneChemistryBiologySignal transductionCell biologyCell cycleCell cultureBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Previously, it has been found that the cancer upregulated gene 2 (CUG2) and the epidermal growth factor receptor (EGFR) both contribute to drug resistance of cancer cells. Here, we explored whether CUG2 may exert its anticancer drug resistance by increasing the expression of EGFR. METHODS: EGFR expression was assessed using Western blotting, immunofluorescence and capacitance assays in A549 lung cancer and immortalized bronchial BEAS-2B cells, respectively, stably transfected with a CUG2 expression vector (A549-CUG2; BEAS-CUG2) or an empty control vector (A549-Vec; BEAS-Vec). After siRNA-mediated EGFR, Stat1 and HDAC4 silencing, antioxidant and multidrug resistance protein and mRNA levels were assessed using Western blotting and RT-PCR. In addition, the respective cells were treated with doxorubicin after which apoptosis and reactive oxygen species (ROS) levels were measured. Stat1 acetylation was assessed by immunoprecipitation. RESULTS: We found that exogenous CUG2 overexpression induced EGFR upregulation in A549 and BEAS-2B cells, whereas EGFR silencing sensitized these cells to doxorubicin-induced apoptosis. In addition, we found that exogenous CUG2 overexpression reduced the formation of ROS during doxorubicin treatment by enhancing the expression of antioxidant and multidrug resistant proteins such as MnSOD, Foxo1, Foxo4, MRP2 and BCRP, whereas EGFR silencing congruently increased the levels of ROS by decreasing the expression of these proteins. We also found that EGFR silencing and its concomitant Akt, ERK, JNK and p38 MAPK inhibition resulted in a decreased Stat1 phosphorylation and, thus, a decreased activation. Since also acetylation can affect Stat1 activation via a phospho-acetyl switch, HDAC inhibition may sensitize cells to doxorubicin-induced apoptosis. Interestingly, we found that exogenous CUG2 overexpression upregulated HDAC4, but not HDAC2 or HDAC3. Conversely, we found that HDAC4 silencing sensitized the cells to doxorubicin resistance by decreasing Stat1 phosphorylation and EGFR expression, thus indicating an interplay between HDAC4, Stat1 and EGFR. CONCLUSION: Taken together, we conclude that CUG2-induced EGFR upregulation confers doxorubicin resistance to lung (cancer) cells through Stat1-HDAC4 signaling.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.063
GPT teacher head0.350
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations41
Published2017
Admission routes1
Has abstractno

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