SUMOylation regulates LKB1 localization and its oncogenic activity in liver cancer
Bibliographic record
Abstract
BACKGROUND: Even though liver kinase B1 (LKB1) is usually described as a tumor suppressor in a wide variety of tissues, it has been shown that LKB1 aberrant expression is associated with bad prognosis in Hepatocellular Carcinoma (HCC). METHODS: Herein we have overexpressed LKB1 in human hepatoma cells and by using histidine pull-down assay we have investigated the role of the hypoxia-related post-translational modification of Small Ubiquitin-related Modifier (SUMO)ylation in the regulation of LKB1 oncogenic role. Molecular modelling between LKB1 and its interactors, involved in regulation of LKB1 nucleocytoplasmic shuttling and LKB1 activity, was performed. Finally, high affinity SUMO binding entities-based technology were used to validate our findings in a pre-clinical mouse model and in clinical HCC. FINDINGS: We found that in human hepatoma cells under hypoxic stress, LKB1 overexpression increases cell viability and aggressiveness in association with changes in LKB1 cellular localization. Moreover, by using site-directed mutagenesis, we have shown that LKB1 is SUMOylated by SUMO-2 at Lys178 hampering LKB1 nucleocytoplasmic shuttling and fueling hepatoma cell growth. Molecular modelling of SUMO modified LKB1 further confirmed steric impedance between SUMOylated LKB1 and the STe20-Related ADaptor cofactor (STRADα), involved in LKB1 export from the nucleus. Finally, we provide evidence that endogenous LKB1 is modified by SUMO in pre-clinical mouse models of HCC and clinical HCC, where LKB1 SUMOylation is higher in fast growing tumors. INTERPRETATION: Overall, SUMO-2 modification of LKB1 at Lys178 mediates LKB1 cellular localization and its oncogenic role in liver cancer. FUND: This work was supported by grants from NIH (US Department of Health and Human services)-R01AR001576-11A1 (J.M.M and M.L.M-C.), Gobierno Vasco-Departamento de Salud 2013111114 (to M.L.M.-C), ELKARTEK 2016, Departamento de Industria del Gobierno Vasco (to M.L.M.-C), MINECO: SAF2017-87301-R and SAF2014-52097-R integrado en el Plan Estatal de Investigación Cientifica y Técnica y Innovación 2013-2016 cofinanciado con Fondos FEDER (to M.L.M.-C and J.M.M., respectively), BFU2015-71017/BMC MINECO/FEDER, EU (to A.D.Q. and I.D.M.), BIOEF (Basque Foundation for Innovation and Health Research): EITB Maratoia BIO15/CA/014; Instituto de Salud Carlos III:PIE14/00031, integrado en el Plan Estatal de Investigación Cientifica y Técnica y Innovacion 2013-2016 cofinanciado con Fondos FEDER (to M.L.M.-C and J.M.M), Asociación Española contra el Cáncer (T.C.D, P·F-T and M.L.M-C), Daniel Alagille award from EASL (to T.C.D), Fundación Científica de la Asociación Española Contra el Cancer (AECC Scientific Foundation) Rare Tumor Calls 2017 (to M.L.M and M.A), La Caixa Foundation Program (to M.L.M), Programma di Ricerca Regione-Università 2007-2009 and 2011-2012, Regione Emilia-Romagna (to E.V.), Ramón Areces Foundation and the Andalusian Government (BIO-198) (A.D.Q. and I.D.M.), ayudas para apoyar grupos de investigación del sistema Universitario Vasco IT971-16 (P.A.), MINECO:SAF2015-64352-R (P.A.), Institut National du Cancer, FRANCE, INCa grant PLBIO16-251 (M.S.R.), MINECO - BFU2016-76872-R to (E.B.). Work produced with the support of a 2017 Leonardo Grant for Researchers and Cultural Creators, BBVA Foundation (M.V-R). Finally, Ciberehd_ISCIII_MINECO is funded by the Instituto de Salud Carlos III. We thank MINECO for the Severo Ochoa Excellence Accreditation to CIC bioGUNE (SEV-2016-0644). Funding sources had no involvement in study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".