MétaCan
Menu
Back to cohort
Record W2088068141 · doi:10.1158/1538-7445.am10-1646

Abstract 1646: Molecular pathways associated with Reolysin and gemcitabine synergy in ras-mutated human HCT116 cells

2010· article· en· W2088068141 on OpenAlexaff
Maureen E. Lane, Nancy Hamel, Sabrina Tachdjian, Matt Coffey, Brad Thompson, Christen Besanceney

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldImmunology and Microbiology
Topicinterferon and immune responses
Canadian institutionsOncolytics Biotech (Canada)
Fundersnot available
KeywordsOncolytic virusIn vivoGeneCell cultureIn vitroGene expressionCancer researchBiologyRNA interferenceInterferonMolecular biologyRNAVirologyVirusBiochemistryGenetics

Abstract

fetched live from OpenAlex

Abstract Reolysin, a type 3 reovirus, is a ubiquitous double-stranded RNA virus that exhibits selective oncolytic activity in ras-activated tumor cells and is non-pathogenic in humans. Our laboratory has previously demonstrated that Reolysin (reo) is synergistic when used in combination with gemcitabine (gem) and other commonly used cytotoxic agents against human colon carcinoma cells in vitro and in vivo. To determine the molecular pathways associated with gem/reo synergy, we exposed HCT116 cells, a human colon carcinoma cell line, to gem, reo, or the combination for 24, 48, 72 and 96 hrs in triplicate. The drug concentrations used were those found to be synergistic in previous in vitro studies (24 pfu/cell reo and/or 4nM gem). We harvested the cells, extracted RNA and performed microarray analysis using the HU133 2.0 plus array (Affymetrix). Gene expression data analysis was performed using GeneSpring GX 7.3.1 (Agilent Technologies). Raw intensity data were imported and preprocessed using the RMA algorithm. Data was then transformed, chips were normalized to the 50th percentile and raw data were filtered with a 2 fold minimum gene expression cutoff. Each experiment was run in triplicate and gene expression levels were averaged among replicates. We performed a 2-way ANOVA to test for time and treatment effects. The genes presenting the most significant treatment effects (160 genes, p<0.01) were uploaded to Ingenuity IPA 6.5 (Ingenuity Systems) for further pathway analysis. The top three canonical pathways significantly affected by the combination treatment were interferon signaling, antigen presentation and the protein ubiquitination pathways. These data suggest that the combination of gem and reo stimulates the immune system to increase surveillance/recognition of cancer cells. Further analyses were performed comparing the combination of gem/reo to gem alone. Approximately 300 genes were significantly (2 fold change, p<0.01) up or down-regulated in the combination therapy compared to gem alone. The combination of gem/reo downregulated PI3Kinase signaling while upregulating IKB signaling. The downstream effects of IKB upregulation are antiviral and stress responses. Single agent gemcitabine has proven to be inactive in colon cancer, yet HCT116 cells treated with a combination of gem and reo proved to be an effective pre-clinical therapy in these experiments. This enhanced preclinical efficacy is potentially due to an enhancement of tumor surveillance by the immune system. Clinical trials with Reolysin in combination with other chemotherapeutic drugs are ongoing. Understanding the mechanisms associated with cytotoxic synergy will allow us to better select drug combinations for specific tumors. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1646.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.029
GPT teacher head0.328
Teacher spread0.299 · 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
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueCancer ResearchSame topicinterferon and immune responsesFrench-language works237,207