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Record W2963877669 · doi:10.3389/fgene.2019.00785

Chicken or Egg: Is Clonal Hematopoiesis Primarily Caused by Genetic or Epigenetic Aberrations?

2019· review· en· W2963877669 on OpenAlexfundno aff
Olivia Cypris, Tanja Božić, Wolfgang Wagner

Bibliographic record

VenueFrontiers in Genetics · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsnot available
FundersRWTH Aachen UniversityDeutsche KrebshilfeBundesministerium für Bildung und ForschungDeutsche ForschungsgemeinschaftElse Kröner-Fresenius-StiftungUniversity of Lethbridge
KeywordsEpigeneticsBiologyEpigenomeChromatinSomatic evolution in cancerGeneticsEpigenetic therapyMutationDNA methylationCancerGene

Abstract

fetched live from OpenAlex

Hematopoietic malignancies, including multiple myeloma, are associated with characteristic mutations and genetic instabilities that drive malignant transformation. On the other hand, tumor formation is also associated with drastic epigenetic aberrations, which can impact on the genetic sequence. Therefore, the question arises if malignant transformation is primarily caused by genetic or epigenetic events. The tight connection of these processes becomes obvious by the fact that in several malignancies, as well as in age-related clonal hematopoiesis, mutations are particularly observed in epigenetic writers such as DNMT3A and TET2. On the other hand, specific epigenetic aberrations, so called “epimutations”, can mimic genomic mutations. In contrast to the genetic sequence, which remains relatively stable throughout life, the epigenome notoriously undergoes drastic changes in normal hematopoietic development and aging. It is conceivable that such epigenetic reorganization, e.g. in 3D chromatin conformation, paves the way for secondary chromosomal instabilities, which then result in tumor-specific genomic changes that further trigger disease progression. This scenario might explain occurrence of tumor-specific mutations particularly in the elderly. Taken together, the causality dilemma is difficult to solve because genetic and epigenetic aberrations are interlinked during disease development. A better understanding of how the chromatin structure or 3D nuclear organization can evoke specific mutations might provide new perspectives for prevention, early diagnostics, and targeted therapy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.873
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.038
GPT teacher head0.320
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations7
Published2019
Admission routes1
Has abstractyes

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