The <i>PAX‐5</i> transcript is submitted to 3'UTR editing which regulates its oncogenic expression in cancer cells
Bibliographic record
Abstract
The Pax‐5 oncogene is a major factor in various cancer lesions such as hematopoietic cancers. Recently, we have also shown that Pax‐5 regulates breast cancer phenotypic transitioning processes (EMT‐MET) leading to the regulation of cancer cell malignancy. To date, the aberrant expression of Pax‐5 in cancer cells is still unknown. Our team has thus turned its attention to the post‐transcriptional regulation of Pax‐5 expression by important regulatory elements such as miRNAs and alternative polyadenylation (APA). Upon our analysis of the Pax‐5 transcript in Pax‐5 bearing cells (breast epithelia and B lymphocytes), we found that not only is the 3'UTR submitted to APA; but also, alternative splicing of the Pax‐5 mRNA 3'UTR. Interestingly, upon rapid amplification of cDNA ends (3'RACE) from polysomal fractions, we found that Pax‐5 3'UTR shortening correlates with increased translation frequency. These observations were also validated using reporter gene assays where various truncated 3'UTRs cloned downstream of a luciferase gene resulted in differentially translational expression. More importantly, we also found that Pax‐5 transcripts characterized with shorter 3'UTRs were also associated with advanced staging of hematopoietic cancer lesions. Our findings identify novel molecular mechanisms, which account for Pax‐5 aberrant expression and function in cancer cells. These findings will further elucidate Pax‐5 ‐mediated cancer processes and may provide new avenues for therapeutic intervention. Support or Funding Information This work was supported by grants from the New Brunswick (NB) Innovation Foundation, the Canadian Breast Cancer Foundation, the Canadian Breast Cancer Society/QEII Foundation, the NB Health Research Foundation and by the Beatrice Hunter Cancer Research Institute This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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) | 0.003 | 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".