Short Telomeres Resulting from Heritable Mutations in the Telomerase Reverse Transcriptase Gene Predispose for a Variety of Malignancies
Bibliographic record
Abstract
Telomeres are composed of long arrays of TTAGGG repeats and associated proteins that act as a protective cap for chromosome ends. The length of telomere repeats is set in the germline but decreases in somatic cells, primarily as a function of DNA replication. Progressive telomere shortening limits stem cell divisions and probably acts as a tumor suppressor mechanism. Using a sensitive PCR method to detect the length of individual telomere repeats on specific chromosomes, we confirmed that telomere length decreases from primitive to more differentiated human cell types within the hematopoietic hierarchy. Genetic mutations in the components of telomerase (the RNA template sequence hTERC, reverse transcriptase hTERT, and Syskerin DKC1) have recently been implicated in a variety of bone marrow failure syndromes, idiopathic pulmonary fibrosis, and more recently, acute myeloid leukemia (AML). The majority of mutations discovered in AML patients were heritable and resulted in partial loss of telomerase activity, a finding counterintuitive to the requirement of telomerase in cancer cells. We have found heritable hypomorphic TERT mutations in other cancers as well, and we propose that such mutations result in short telomeres and premature loss of stem cells. Loss of normal stem cells could provide strong selection for abnormal cells incapable of responding to DNA damage signals originating from short telomeres. Such cells will have a DNA repair defect resulting in genomic instability and a mutator phenotype. Our findings point to an intimate connection between senescence and cancer and highlight the important role of telomeres in the biology of normal and malignant human cells.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".