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Record W4379984278 · doi:10.1158/1538-7445.am2023-1217

Abstract 1217: The <i>FAM72</i> gene family promotes cancer development by disabling the base excision repair system

2023· article· en· W4379984278 on OpenAlexaff
Yuqing Feng, Bhupesh Kumar Thakur, Jeffery Bruce, Sami Mamand, Melika Shirdarreh, Matthew Wong, Jennifer Silvester, Ming Han, Mohammad Abul Kashem, Amin Zia, David W. Cescon, T. S. Pugh, Rossanna C. Pezo, Alberto Martín

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsSunnybrook Health Science CentreUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsDNA glycosylaseBiologyCarcinogenesisBase excision repairDNA repairCancerCancer researchGeneDNA damageMUTYHMutationUracil-DNA glycosylaseTumor progressionDNA mismatch repairGeneticsDNA

Abstract

fetched live from OpenAlex

Abstract Genetic lesions are central contributors to cancer development and progression, and understanding the sources of these lesions will provide a better understanding of the mechanisms of carcinogenesis. Our previous work showed that the uncharacterized murine Fam72a gene promotes mutagenic DNA repair during antibody maturation by causing the degradation of Uracil DNA glycosylase 2 (UNG2), a component of the base excision repair (BER) system. Humans encode four almost identical paralogues of FAM72 called FAM72A-D, which are absent in all other mammalian genomes, including those of non-human primates. The role of these four paralogues in human biology is unknown. Intriguingly, a previous report showed that FAM72A is over-expressed in many cancers. Since FAM72A promotes mutagenesis by degradation of UNG2, we hypothesized that overexpression of the FAM72 gene family might promote cancer development and progression. Here we show that FAM72A-D is overexpressed in many human cancers and inversely correlates with UNG2 protein levels in tumorigenic tissue. However, FAM72A but not FAM72B-D causes degradation of UNG2. Consistent with this effect, FAM72 expression correlates with a higher mutation load in many tumor types. Since genetic mutations are associated with cancer development and progression, we tested whether FAM72 expression is associated with disease outcomes. Indeed, we found that high FAM72 expression was associated with poorer survival in several cancers. To directly test if Fam72a is sufficient to promote cancer, we generated transgenic mice that overexpress Fam72a in multiple tissues. We observed that Fam72a overexpression promotes increased colonic polyps in the Apcmin background compared to controls. These data show that the novel FAM72 gene family are drivers of cancer development in both mice and humans and advances our understanding of the underlying molecular mechanisms that precipitate cancer development and progression. This work is supported by a grant from the CIHR (PJT-180269). Citation Format: Yuqing Feng, Bhupesh Thakur, Jeffery Bruce, Sami Mamand, Melika Shirdarreh, Matthew Wong, Jennifer Silvester, Ming Han, Mohammad Kashem, Amin Zia, David Cescon, Tervor Pugh, Rossanna C. Pezo, Alberto Martin. The FAM72 gene family promotes cancer development by disabling the base excision repair system [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1217.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.094
GPT teacher head0.386
Teacher spread0.292 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations1
Published2023
Admission routes1
Has abstractyes

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