Stable Suppression of a Novel Oncogene, AHI-1, in Human Cutaneous T-Cell Leukemia Cells Normalizes Its Transforming Activity In Vitro and In Vivo and Aberrant Expression of AHI-1 Is Also Present in Leukemic Sezary Cells from Patients with Sezary Syndrome.
Bibliographic record
Abstract
Abstract Ahi-1 (Abelson helper integration site 1) is a novel gene that is commonly activated by provirus insertional mutagenesis in v-abl and myc-induced murine leukemias and lymphomas. It encodes a unique protein with SH3 and WD40-repeat domains suggesting novel signaling activities. Involvement of Ahi-1 in leukemogenesis is suggested by the high frequency of Ahi-1 mutations seen in certain virus-induced murine leukemias and lymphomas and by the gross perturbations seen in the expression of human AHI-1 and its isoforms in several human leukemia cell lines, particularly in the cutaneous T-cell leukemia cell lines, Hut 78 and Hut 102, where increases in AHI-1 transcripts of 40-fold are seen. To test directly whether the deregulated expression of AHI-1 in leukemic cells contributes to their transformed properties, knockdown of AHI-1 expression in Hut 78 cells, a cell line derived from peripheral blood of a patient with Sezary syndrome, was performed using retroviral-mediated RNA interference (RNAi). In a screen of 9 constructs that produce specific short hairpin AHI-1 transcripts, one was found to specifically inhibit AHI-1 expression in transduced Hut 78 cells by 80%, as evaluated by quantitative real-time RT-PCR, Northern and Western blot analyses. Retroviral-mediated suppression of AHI-1 also reduced the autocrine production of IL-2, IL-4 and TNFalpha in Hut 78 cells by up to 85% and caused a significant reduction in their growth factor independence in semi-solid cultures (up to 10-fold) and in single cell cultures (4-fold) by comparison to cells transduced with a control vector. Interestingly, although addition of IL-4, TNFalpha or a combination of 3 growth factors restored colony formation from the shRNA-transduced Hut 78 cells in semi-solid cultures, this was not achieved if only IL-2 was added, even though AHI-1 expression was inhibited. The ability of Hut 78 cells to produce tumors in NOD/SCID-β2microglobulin−/− mice within 3 weeks was also lost when AHI-1 expression was suppressed. Microarray analysis on RNA from Hut 78 cells with the suppression of AHI-1, using the Affymetrix Human Genome U133 plus 2.0 Arrays, identified differentially expressed molecules critical in T-cell activation, signal transduction, as well as cell proliferation and differentiation. Q-RT-PCR analysis revealed that the transcript levels of AHI-1 and its isoforms were significantly increased in CD4+CD7− Sezary cells, in which more than 85% of these cells are leukemic cells, in 5 of 6 blood samples obtained from patients with Sezary syndrome as compared to T cells similarly isolated from 8 healthy individuals. Elevated AHI-1 transcript levels were not found in 3 patient samples containing less than 35% leukemic Sezary cells. Taken together, these findings provide strong evidence of the oncogenic activity of AHI-1 in human T-cell leukemic cells and its deregulation can contribute to the development of human cutaneous T-cell lymphomas, including Sezary syndrome.
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 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".