Lentivirus-mediated down-regulation of CK2α inhibits proliferation and induces apoptosis of malignant lymphoma and leukemia cells
Bibliographic record
Abstract
Casein kinase II subunit alpha (CK2α) is highly expressed in many malignant tumor tissues, including lymphomas and leukemia. To investigate the role of CK2α in cell proliferation and apoptosis of malignant lymphomas and leukemia, 2 lymphoma cell lines and one leukemia cell line were infected with CK2α shRNA lentivirus or negative control shRNA lentivirus, and stably infected cell lines were established. Real-time PCR and Western blot results showed that the mRNA and protein levels of CK2α were significantly reduced in CK2α knockdown cells. The tetrazolium-based colorimetric (MTT) assay found that down-regulation of CK2α inhibited the proliferation of these cells. Flow cytometry analysis showed that inhibition of CK2α induced cell cycle arrest and apoptosis of lymphoma and leukemia cells. In accordance with these, down-regulation of CK2α also reduced the protein levels of proliferating cell nuclear antigen (PCNA), cyclinD1, and bcl-2, and increased the protein expression of bax, cleaved caspase-3, cleaved caspase-9, and cleaved poly(ADP ribose) polymerase (PARP). Moreover, knockdown of CK2α impeded the growth of xenograft tumors in vivo. In summary, our study revealed that CK2α may contribute to the development of malignant lymphoma and leukemia, and serve as the therapeutic target of these malignant tumors.
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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 | 0.001 |
| 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".