Abstract 4762: ITPKA expression in lung and other cancers, regulated via gene body methylation, functions as an oncogene
Bibliographic record
Abstract
Abstract Inositol-Trisphosphate 3-Kinase A (ITPKA), a kinase with limited tissue distribution, is involved in inositol phosphate metabolism. We identified ITPKA as up-regulated in lung and many other types of cancers. Using gain-of-function and loss-of-function approaches, we demonstrated by in vitro and in vivo assays that ITPKA functions as an oncogene to drive the development of lung cancer. We further showed that methylation level in the ITPKA gene body is significantly higher in various types of primary tumors than in corresponding non-malignant tissues, which was positively correlated with its expression. Our study revealed that DNMT3B-mediated methylation of the CpG island in ITPKA gene body regulates its expression via modulation of the binding of transcription activator SP1 to the ITPKA promoter. During the multistage pathogenesis of lung carcinoma, ITPKA gene body methylation first appeared at the in situ carcinoma stage and increased during disease progression. Thus ITPKA expression functions as an oncogene in lung and other cancers. Highly specific and sensitive expression and methylation of ITPKA was present in a wide range of tumor types, suggesting that deregulation of ITPKA may function as a universal or near universal hallmark of malignancy. Citation Format: Yi-Wei Wang, Xiaotu Ma, Yu-An Zhang, Mei-Jung Wang, Yasushi Yatabe, Stephen Lam, Luc Girard, Jeou-Yuan Chen, Adi F. Gazdar. ITPKA expression in lung and other cancers, regulated via gene body methylation, functions as an oncogene. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4762. doi:10.1158/1538-7445.AM2015-4762
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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 | 0.000 | 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) | 0.004 | 0.001 |
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".