Abstract LB-305: Identification of p21 as a novel substrate of LATS2 in lung cancer
Bibliographic record
Abstract
Abstract LATS2 is a serine/threonine kinase and tumor suppressor gene found to be downregulated and mutated in lung cancer. Although LATS2 has been shown to regulate many cancer-related functions such as maintenance of genomic stability, cell proliferation and apoptosis, its roles in lung tumorigenesis are largely unknown. In addition, the downstream cellular genes mediating LATS2 tumor suppressing function in lung cancer remains elusive. Since LATS2 kinase activity is essential for its function, therefore, identification and characterization of LATS2 substrates is critical in understanding the role it plays in lung tumorigenesis and is the focus of this study. To elucidate LATS2 function in lung cancer, we stably overexpressed LATS2 in a variety of lung cancer cell lines using a doxycycline-inducible lentivirus system. We have found that LATS2 strongly suppresses cell proliferation in all of cell lines tested. Further functional screening for LATS2 kinase substrates identified p21CIP1 to be a potential LATS2 substrate mediating LATS2 tumor suppressing function. p21 and LATS2 were found to bind each other as revealed by GST-pulldown and co-immunoprecipitation assays. Importantly, we found that LATS2 specifically phosphorylates p21 at S146, and that this site is critical for suppressing cell proliferation in lung cancer cells. These findings describe a novel LATS2 signalling pathway and improve our understanding of the role of LATS2 in lung tumorigenesis. Citation Format: Benjamin Yeung. Identification of p21 as a novel substrate of LATS2 in lung cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr LB-305. doi:10.1158/1538-7445.AM2014-LB-305
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".