Faculty Opinions recommendation of Paradoxical association of TET loss of function with genome-wide DNA hypomethylation.
Bibliographic record
Abstract
Cancer genomes are characterized by focal increases in DNA methylation, co-occurring with widespread hypomethylation. Here, we show that TET loss of function results in a similar genomic footprint. Both 5hmC in wild-type (WT) genomes and DNA hypermethylation in TET-deficient genomes are largely confined to the active euchromatic compartment, consistent with the known functions of TET proteins in DNA demethylation and the known distribution of 5hmC at transcribed genes and active enhancers. In contrast, an unexpected DNA hypomethylation noted in multiple TET-deficient genomes is primarily observed in the heterochromatin compartment. In a mouse model of T cell lymphoma driven by TET deficiency (Tet2/3 DKO T cells), genomic analysis of malignant T cells revealed DNA hypomethylation in the heterochromatic genomic compartment, as well as reactivation of repeat elements and enrichment for single-nucleotide alterations, primarily in heterochromatic regions of the genome. Moreover, hematopoietic stem/precursor cells (HSPCs) doubly deficient for Tet2 and Dnmt3a displayed greater losses of DNA methylation than HSPCs singly deficient for Tet2 or Dnmt3a alone, potentially explaining the unexpected synergy between DNMT3A and TET2 mutations in myeloid and lymphoid malignancies. Tet1-deficient cells showed decreased localization of DNMT3A in the heterochromatin compartment compared with WT cells, pointing to a functional interaction between TET and DNMT proteins and providing a potential explanation for the hypomethylation observed in TET-deficient genomes. Our data suggest that TET loss of function may at least partially underlie the characteristic pattern of global hypomethylation coupled to regional hypermethylation observed in diverse cancer genomes, and highlight the potential contribution of heterochromatin hypomethylation to oncogenesis. PMID: 31371502 Funding information This work was supported by: NCRR NIH HHS, United States Grant ID: S10 RR027366 NIH HHS, United States Grant ID: S10 OD016262 NCI NIH HHS, United States Grant ID: R35 CA210043
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.448 | 0.255 |
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".