Microarray Identification of Differentially Expressed Genes in AHI-1- Mediated Leukemic Transformation of Human Cutaneous T-Cell Lymphoma Cells.
Bibliographic record
Abstract
Abstract Abelson helper integration site 1 (Ahi-1) is a recently identified oncogene which is often the target of provirus insertional mutagenesis in murine leukemias and lymphomas. Ahi-1/AHI-1 encodes a unique cell signaling protein with a SH3 domain, multiple SH3 binding sites, seven WD40 repeats and a number of potential tyrosine kinase phosphorylation sites. Its involvement in human leukemogenesis is demonstrated by gross perturbations in its expression in several leukemic cells lines, particularly in cutaneous T-cell lymphoma (CTCL) cell lines (Hut 78 and Hut 102) where 40-fold up-regulation of AHI-1 transcripts is seen. Hut78 cells are derived from a patient with Sezary syndrome, a common leukemic variant of human CTCL. Interestingly, we have recently demonstrated that aberrant expression of AHI-1 at both RNA and protein levels is found in CD4+CD7− leukemic Sezary cells from patients with Sezary syndrome. Moreover, stable suppression of AHI-1 using retroviral-mediated RNA interference in Hut 78 cells reduces autocrine production of interleukin (IL)-2, IL-4 and tumor necrosis factor-alpha (TNFα) and normalizes their transforming activity both in vitro and in vivo. In an effort to identify genes involved in AHI-1-mediated leukemic transformation in CTCL, Microarray analysis was performed using the Affymetrix Human Genome U133 plus 2.0 Arrays which contains over 47,000 transcripts (54,330 probes). Comparative analysis of six RNA samples from AHI-1/sh4 cells (knockdown of AHI-1) and five samples from Hut 78 and Hut 78 cells transduced with a control vector (RPG) demonstrated that 101 genes (119 probes) were statistically differentially expressed with fold changes > or < 2 at p-values ≤ 0.001, using a DNA-Chip Analyzer (dChip). With the same selection criteria, the Linear Model for Microarray Data (Limma) analysis initially listed 239 genes (283 probes). Once the p-values for these genes were adjusted, using the approach of Benjamini and Hochberg, the list was refined to 27 genes (33 probes). After evaluation of differentially expressed genes selected by both dChip and Limma analyses, 15 up-regulated genes (fold change range: 2.2–11) and 6 down-regulated genes (fold change range: 2.1–8.3) in AHI-1 suppressed Hut 78 cells as compared to control cells, were chosen for further analysis. The expression patterns of these 21 genes identified by Microarray analyses were confirmed by quantitative real-time RT-PCR (fold change range: 6.7 higher to 33.3 lower, p≤0.001). Significant down-regulation of AHI-1 itself (p≤0.001) was confirmed in all six AHI-1/sh4 RNA samples studied. Interestingly, functional grouping of differentially expressed genes in AHI-1/sh4 cells shows several are involved in signal transduction (BRDG1, HCK, and REPS2), cell cycle control (CCNG2, CDKN1C, and PDCD6), cell proliferation and differentiation (BIN1 and MLLT11) and mRNA stability (ELAVL1). Additionally, our observed deregulated expression of NKG7 has also recently been documented in both Sezary syndrome and mycosis fungoides patient samples. Further, candidate tumor suppressor genes (BIN1 and CDKN1C) were found to be highly elevated in AHI-1/sh4 cells where AHI-1 expression is stably inhibited. These findings indicate that we have identified several new differentially expressed genes that may play critical roles in alteration of T-cell signaling 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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".