Characterization of the Role of the Tumor Suppressor BIN1 as a Potential Mediator of the AHI-1 Oncogene in Human Cutaneous T-Cell Lymphomas
Bibliographic record
Abstract
Abstract Abstract 5229 Cutaneous T-cell lymphomas (CTCLs) represent a group of lymphoproliferative disorders that are characterized by the homing of malignant T-cells to the surface of skin. There are two main types of CTCL: Mycosis Fungoides (MF) and its leukemic variant Sezary Syndrome (SS), which together represent ∼65–70% of all CTCL cases. The precise genetic pathogenesis of these diseases remains largely undetermined. Recently, our research group has demonstrated that AHI-1 (Abelson Helper Integration site-1) oncogene is involved in CTCL. AHI-1 is often the target of provirus insertional mutagenesis in a number of murine leukemias and lymphomas. High expression of AHI-1 is also observed in human leukemia cell lines, with marked upregulation (up to 40 fold) in CTCL lines (Hut78 and Hut102). Moreover, in FACS-purified CD4+CD7− Sezary cells from patients with Sezary Syndrome, AHI-1 has higher expression at both the RNA and protein levels compared to normal CD4+ cells. Furthermore, stable suppression of endogenous AHI-1 in Hut78 cells using small interfering RNA (AHI-1/sh4), reduces autocrine production of interleukin-2 (IL-2), IL-4 and tumor necrosis factor-alpha, and normalizes their transforming activity both in vitro and in vivo. Thus, lymphomagenic activity of Hut78 cells is partially dependent on the expression of AHI-1. Several differentially expressed genes that may play critical roles in AHI-1-mediated leukemic transformation in Hut78 cells have recently been identified through microarray analysis. One candidate is BIN1 (Bridging integrator 1), a tumor suppressor gene which is inactivated or deleted in various cancers. BIN1 protein interacts directly with c-MYC oncogene and inhibits c-MYC–mediated transactivation and transformation. Overexpression of BIN1 increases cell death and decreases cell proliferation in transformed cells. Furthermore, a recent study demonstrated that BIN1 sustains cancer cell sensitivity to some chemotherapy drugs. However, the role of BIN1 in regulation of normal hematopoiesis and lymphomagenesis remains unknown. In our study, BIN1 was shown to be up-regulated at both RNA and protein levels in AHI-1/sh4 cells compared to control Hut78 cells and these data were further confirmed at the mRNA level in primary CD4+CD7− SS cells. It has also been demonstrated that overexpression or suppression of AHI-1 mediate expression changes of BIN1, suggesting that the BIN1 is a potential co-operator of the AHI-1 oncogene. To investigate the tumor suppressor activity of BIN1 in Sezary cells and its potential molecular connection to AHI-1, full-length BIN1 was overexpressed in Hut78 (BIN1/Hut78) and AHI-1/sh4 cells using a lentiviral vector. Increased transcript levels and protein expression of BIN1 were confirmed in transduced cells compared to controls by Q-RT-PCR and Western analysis, respectively. Interestingly, significant reduction in cell proliferation was observed in BIN1/Hut78 cells compared to controls using the 3H- Thymidine uptake assay (>20% reduction in radioactive signal, p= 0.01). These results were further confirmed by using the colony forming cell (CFC) assay and observing a 40% reduction in colony numbers in BIN1/Hut78 cells compared to controls. Furthermore, a significant increase in the number of apoptotic cells was observed in BIN1/Hut78 cells compared to controls after culturing the cells for 48 hours in serum-free conditions using 7-amino-actinomycin D and PE-conjugated AnnexinV antibody staining (∼17% increase, p=0.03). No significant difference was observed in BIN1-transduced AHI-1/sh4 cells compared to controls, possibly due to high expression of endogenous level of BIN1 in these cells. To further investigate the effect of BIN1 on chemoresistance, Hut78 and BIN1/Hut78 cells were treated with different dosages of chemotherapeutic drugs (e.g. Etoposide) and the number of viable cells was counted after specific time points using the Trypan blue exclusion assay. Significant reduction in the number of viable cells was observed in BIN1/Hut78 cells compared to controls after 24 hours of drug treatment (∼20% reduction in cell viability, p=0.03). These findings suggest anti-proliferative and pro-apoptotic roles for BIN1 in human CTCL cells, and that restoration of BIN1 could potentially mediate the chemoresistance of these cells. Disclosures: No relevant conflicts of interest to declare.
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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) | 0.002 | 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".