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THE DUAL ACTIONS OF DNA REPAIR ENZYME, PARP‐1, IN COLON INFLAMMATION AND CARCINOGENESIS

2016· article· en· W4389034252 on OpenAlexfundno aff
Abdelmetalab Tarhuni, Youssef Errami, Ali H. El‐Bahrawy, Amir A. Al-Khami, Mohamed Gohnim, Amarjit S. Naura, Matthew J. Dean, Kusma Pyakurel, Jeffrey Wang, Hassan Brim, Hassan Ashktorab, Paulo C. Rodrı́guez, Augusto C. Ochoa, Hamid Boulares

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsnot available
FundersNational Institutes of HealthCanadian Bureau for International Education
KeywordsCarcinogenesisCancer researchGenome instabilityColorectal cancerDNA repairPoly ADP ribose polymeraseMouse model of colorectal and intestinal cancerInflammationAdenomatous polyposis coliBiologyDNA damageCancerImmunologyPolymeraseGeneticsDNA

Abstract

fetched live from OpenAlex

Colon cancer is one of the leading causes of death in the United States. Genomic instability and chronic colonic inflammation are the main causes of colon cancer. Mutation in any of the components of the β‐catenin destruction complex, mainly in adenomatous polyposis coli (APC) protein, leads to over proliferation of colon epithelial cells and may result in tumor formation in the colon or rectum. Additionally, chronic inflammatory diseases such colitis upregulate inflammatory markers that may inhibit DNA repair enzymes, cause aberrant activation of β‐catenin, and induce mutation and activation of transcription factors such as STAT3 and NF‐κB. These events lead to uncontrolled cell proliferation and may cause colon tumor formation. Poly‐(ADP‐ribose)‐polymerase I (PARP‐1) is an enzyme that is critically involved in several cellular processes such as DNA repair, apoptosis, genomic stability, and inflammation. Because PARP‐1 plays a role in colon tissue homeostasis, inhibition of PARP‐1 may promote colon carcinogenesis by inhibiting DNA repair and causing genomic instability. On the other hand, our lab has previously shown that PARP‐1 inhibition results in reduced inflammation in both acute and chronic models of inflammatory diseases, which gives us additional evidence that PARP‐1 contributes to colon carcinogenesis. I thus hypothesize that inhibition of PARP‐1 (A) may promote colon tumorigenesis if genomic stability is the predominant driver in colon carcinogenesis but (B) may reduce colon tumorigenesis if inflammation is the major driver of the disease. To test this hypothesis I have used three animal models: the Apc Min/+ mouse model, which develops spontaneous intestinal tumors; a combined carcinogen based/chronic inflammation induced (AOM+DSS) model; and an MCA‐38 cell based allograft model. When genetic mutation is the primary driver of carcinogenesis (as in the Apc Min/+ mouse model), inhibition of PARP‐1 function through gene deletion resulted in a reduced tumor burden in heterozygous (Apc Min/+ /PARP +/− ) mice, but an increased tumor burden in homozygous (Apc Min/+ /PARP −/− ) mice. In support of this, inhibition of PARP‐1 by olaparib (a PARP‐1 inhibitor used in clinical trials) reduced intestinal tumor burden in Apc Min/+ /PARP +/+ mice. Both genetic and pharmacological inhibition of PARP‐1 suppressed inflammation as evaluated by inflammatory markers (iNOS, VCAM‐1, and TNF‐a), and, in our chronic inflammation driven model (AOM/DSS), PARP‐1 knockout showed significant reduction in colon tumorigenesis compared to wild type mice. PARP‐1 nullizigosity promoted a tumor‐suppressive rather than a tumor‐promoting host response as shown by our MCA‐38‐ allograft data. Taken together, these data reveal that, while PARP‐1 is an attractive candidate for therapeutics due to its clear role in the two primary processes leading to colon cancer development, more work has to be done to determine which specific conditions are necessary for PARP‐1 inhibition to reduce – rather than promote ‐ tumorigenesis. Support or Funding Information ACS, NIH, Stanley S. Scott Cancer Center, and CBIE

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.032
GPT teacher head0.294
Teacher spread0.262 · 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 designObservational
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
Published2016
Admission routes1
Has abstractyes

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