MétaCan
Menu
Back to cohort

Abstract C147: siRNA targeting TS and TK as an anticancer therapy

2009· article· en· W2332272456 on OpenAlexaff
Christine Di Cresce, René Figueredo, James Koropatnick

Bibliographic record

VenueMolecular Cancer Therapeutics · 2009
Typearticle
Languageen
FieldMedicine
TopicCholangiocarcinoma and Gallbladder Cancer Studies
Canadian institutionsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsSmall interfering RNAThymidylate synthaseBiologyCancer researchCell growthMolecular biologyTransfectionPharmacologyCancerCell cultureBiochemistry

Abstract

fetched live from OpenAlex

Abstract Thymidylate synthase (TS) is the only de novo source of thymidylate (dTMP) for DNA synthesis, repair and proliferation. Cytosolic thymidine kinase 1 (TK1) and mitochondrial thymidine kinase 2 (TK2) represent “scavenger” pathways for alternative production of essential dTMP by phosphorylation of intracellular thymidine (Thd). Both TS and TKs are upregulated in multiple human tumors, supporting a role for both in malignancy. Drugs targeting TS-protein are a mainstay in cancer treatment but toxicity to normal tissues and tumor cell drug resistance limit their effectiveness. We hypothesize that, when TS-protein is inhibited, the capacity of TKs to generate dTMP may modulate resistance to anti-TS drugs. Antisense molecules, including oligonucleotides (ODNs) and siRNAs, can selectively target specific mRNAs (including TS and TK mRNAs) encoding proteins mediating drug resistance. We have previously reported that antisense ODNs targeting TS inhibit human tumor cell growth in vitro and in immunocompromised host mice, and antisense TS ODNs and siRNAs enhance the growth inhibitory effects of TS-targeting drugs. Antisense TS, therefore, is an attractive candidate for development as an anticancer drug, both alone and in combination with drugs targeting TS protein (raltitrexed, pemetrexed, 5FUdR, and others). The ability of antisense TS drugs to inhibit tumor cell growth and response to other TS-targeting drugs does not correlate with the degree of antisense downregulation of TS mRNA, suggesting that factors other than TS attenuate antitumor effects. We used siRNAs targeting TK1 or TK2 to knock down TK expression in attempt to reduce human tumor cell growth when targeting TKs alone, in combination with siRNAs targeting TS, and in combination with TS siRNA and the anti-TS protein drug 5FUdR. We report that TK and TS levels are highly variable among a panel including human cervical (HeLa) and breast carcinoma (MCF7), colorectal cancer (HT-29) and human mesothelioma cell lines. Furthermore, 24 hrs post-transfection, siRNAs targeting TK1 or TK2 reduce targeted TK-mRNA by greater than 85% at concentration of 5 nM in human cervical carcinoma (HeLa) and human breast carcinoma (MCF7) cells. At 96 hrs post-transfection, siRNA targeting TK1 or TK2 do not independently reduce human tumor cell growth in vitro. Furthermore, simultaneous siRNA targeting of TS and TK effectively, independently, and non-antagonistically reduce both TS and TK mRNA. Antisense targeting TK1 or TK2 alone, unlike siRNA targeting TS alone, does not enhance the capacity of 5FUdR to inhibit human tumor cell growth in vitro. We suggest, however, that combined antisense targeting of TS and TK1/TK2 (particularly under conditions where extracellular thymidine levels are high) will be more effective than either used alone to reduce tumor cell growth and sensitize them to the effects of antitumor TS-targeting chemotherapeutics. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):C147.

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 score0.003
Threshold uncertainty score0.009

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.033
GPT teacher head0.328
Teacher spread0.295 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueMolecular Cancer TherapeuticsSame topicCholangiocarcinoma and Gallbladder Cancer StudiesFrench-language works237,207