Identification of tyrosine kinase, HCK, and tumor suppressor, BIN1, as potential mediators of AHI-1 oncogene in primary and transformed CTCL cells
Bibliographic record
Abstract
AHI-1 is an oncogene often targeted by provirus insertional mutagenesis in murine leukemias and lymphomas. Aberrant expression of human AHI-1 occurs in cutaneous T-cell lymphoma (CTCL) cells and in CD4(+)CD7(-) Sezary cells from patients with Sezary syndrome. Stable knockdown of AHI-1 using retroviral-mediated RNA interference in CTCL cells inhibits their transforming activity in vitro and in vivo. To identify genes involved in AHI-1-mediated transformation, microarray analysis was performed to identify differentially expressed genes in AHI-1-suppressed CTCL cells. Fifteen up-regulated and 6 down-regulated genes were identified and confirmed by quantitative reverse transcription-polymerase chain reaction. Seven were further confirmed in a microarray analysis of CD4(+)CD7(-) Sezary cells from Sezary syndrome patients. HCK and BIN1 emerged as new candidate cooperative genes, with differential protein expression, which correlates with observed transcript changes. Interestingly, changes in HCK phosphorylation and biologic response to its inhibitor, dasatinib, were observed in AHI-1-suppressed or -overexpressed cells. The tumor suppressor BIN1 physically interacts with MYC in CTCL cells, which also exhibit differential MYC protein expression. In addition, aberrant expression of alternative splicing forms of BIN1 was observed in primary and transformed CTCL cells. These findings indicate that HCK and BIN1 may play critical roles in AHI-1-mediated leukemic transformation of human CTCL cells.
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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) | 0.001 | 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 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".