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Record W6999180261

Characterization of loss of HLTF function in the development of colon cancer

2012· dissertation· en· W6999180261 on OpenAlexaff

Bibliographic record

VenueMspace (University of Manitoba) · 2012
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChromatin Remodeling and Cancer
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsKnockout mouseTranscription factorDNA damageMutantTumor suppressor geneTransgene
DOInot available

Abstract

fetched live from OpenAlex

Helicase-like Transcription Factor (HLTF) is a DNA helicase protein which is homologous to SNF/SWI family. It has been demonstrated to be a functional homolog of yeast Rad5, required for the maintenance of genomic stability. Although the physiologic role of HLTF is largely unknown,inactivation of HLTF by promoter hypermethylation has been found in more than 40% human colon cancers. In this study, we have applied mouse transgenic approaches to determine whether loss of HLTF function could be important for colorectal carcinogenesis. HLTF knockout mice were generated by the deletion of first 5 exons of the HLTF gene. The complete loss of HLTF expression in HLTF -/- mice was confirmed by northern blot and real time RT-PCR assays. HLTF -/- mice did not show any developmental defects within a 2-year observation indicating that HLTF is dispensable for mouse development. Furthermore, HLTF -/- mice were free of intestinal or colorectal tumors or other types of tumors, suggesting that loss of HLTF function alone is not sufficient to drive oncogenic transformation in intestinal track and other tissues. To determine whether loss of HLTF function could cooperate with other tumor suppressors in the formation of colorectal cancers, we have bred HLTF knockout mice with the mutant mice for APC (adenomtous polyposis coli) and P53. In HLTF -/-APC Min/+ mice, a significantly increased formation of intestinal adenocarcinoma and colorectal cancers were observed. Although very few HLTF -/-P53 -/- mice developed colorectal cancers, these mice had increased incidence of the formation of metastatic lymphomas. Cytogenetic analysis of colorectal cancer cells derived from HLTF -/-APC Min/+ mice demonstrated a high incidence of gross chromosomal instabilities, including Robertsonian fusions, fragments and aneuploidy. All these genetic alterations were not observed in the intestinal tumor cells from APC Min/+, implicating that loss of HLTF function could induce genomic instability which contributes to intestinal carcinogenesis. To further investigate the role of HLTF in colorectal carcinogenesis, we have also applied a shRNA knockdown approach to down-regulate HLTF expression in human HCT-116 colon cancer cells. HCT-116 cells highly express HLTF and show less chromosomal instability, making these cells as a very useful model to investigate the loss of function of HLTF in human colorectal carcinogenesis. Using Western blot approach, we confirmed that HLTF knockdown HCT-116 cells had less than 5% of HLTF expression as compared to the scramble controls. By inoculating HLTF knockdown HCT-116 cells to Rag1 -/-IL2 -/- immunocompromised mice, we further demonstrated that HLTF knockdown promote tumor growth and invasion. Moreover, spectral karyotyping analysis revealed that HLTF knockdown human colon cancer cells had significantly increased chromosomal instability, including both aneuploidy and chromosomal translocation. Taken together, our work strongly indicates that loss of HLTF function can promote the malignant transformation of intestinal or colonic adenomas to carcinomas by inducing genomic instability. Given the high frequency of epigenetic inactivation by hypermethylation of HLTF in human colon cancers, our studies strongly suggest that this epigenetic alteration could be directly involved in the development of colorectal cancer rather than a consequence of this carcinogenesis.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.012
GPT teacher head0.220
Teacher spread0.208 · 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.

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

Citations0
Published2012
Admission routes1
Has abstractyes

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