Disordered Expression of HIPK Family Members in MDS and AML.
Bibliographic record
Abstract
Abstract The homeodomain interacting protein kinases (HIPKs) are a group of three nuclear serine/threonine protein kinases originally identified as corepressors for various homeodomain-containing transcription factors. The physiological roles of these kinases are largely unknown, though HIPK1 was reported to be a p53-binding protein and might play a role in tumorgenesis. HIPK2 promotes apoptosis via pathways including p53, transcriptional corepressor CtBP, and Wnt-1 signalling. HIPK2 maps to chromosome 7q32-34 and resides within one of the minimal deleted regions of 7q in acute myelogenous leukemia (AML) and myelodysplastic syndrome (MDS). Finally, HIPK3 was first identified as a putative multidrug resistant protein and was reported to be elevated by JNK in prostate cancer cells, thus contributing to increased resistance to Fas-mediated apoptosis. We have utilized Real-Time PCR to investigate the expression of HIPKs in bone marrow from patients with AML (19 patients), MDS (15 patients), chronic myelomonocytic leukemia (CMML, 5 patients), and 11 normal CD34+ mobilized peripheral blood progenitors. The mRNA expression of HIPK1 was higher in AML (P=0.00002), CMML (P=0.02), and MDS (P=0.029) compared to normal. There was also a significant difference in HIPK1 expression between AML and MDS, higher in AML (P=0.009). HIPK2 expression was variable in AML, MDS and CMML patients, while in normal CD34+ cells its expression was consistently low. HIPK3 expression was high in AML compared to normal (P=0.019), but in CMML and MDS its expression was similar to normal. We utilized the AML cell lines HL-60, NB4, and U937 to analyze changes in HIPKs expression during myeloid differentiation. HIPK2 expression significantly increased during ATRA-induced granulocytic differentiation of HL-60 and NB4 cells, but no significant change was seen in Vitamin D3-induced monocytic differentiation of U937 cells. Subgroup analysis of public domain microarray data( Valk et al, NEJM, 2004) indicates that HIPK2 expression is lower in AML patients with -7/-7q compared to other AML patients. We hypothesize that loss of HIPK2 expression contributes to the chemoresistance of -7/-7q AML by impairing normal apoptosis. As an initial test of this hypothesis we have studied the effect of forced expression of HIPK2 on sensitivity of COS-7 cells to daunorubicin, cytarabine and etoposide. COS-7 cells transfected with HIPK2 are more sensitive to daunorubicin with the inhibition rate of growth of 28.31% at 1.6 μg/ml daunorubicin after 48h incubation, while the inhibition rate of COS-7 cell transfected with dominant negative (DN)-HIPK2 (18.80%) was similar to cells transfected with an empty vector (14.96%) and untransfected cells (15.12%) under the same condition of drug exposure. Similar results were found for cytarabine, where the inhibition rate of growth was 17.40% (HIPK2), 9.00% (DN-HIPK2), 6.41% (empty vector), 5.77% (untransfected control). No change of sensitivity was found for etoposide. Conclusions: The anti-apoptotic kinases HIPK1 and HIPK3 are highly expressed in AML, and might have roles in leukemogenesis. HIPK2 shows heterogeneous expression in AML but is underexpressed in AML patients with -7q, and mediates sensitivity to cytarabine- and daunorubicin-induced apoptosis. The possible roles of HIPKs in normal and leukemic hematopoiesis require further investiagtion.
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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".