Abstract 3586: Reactive oxygen species and antioxidant pathway in resistance to doxorubicin and paclitaxel in cancer
Bibliographic record
Abstract
Abstract Introduction: Resistance to anthracyclines and taxanes are the most challenging issue in breast cancer treatment. Genetic variations account for the observed inefficacy of the chemotherapy in breast cancer patients. Aim: In this study we aimed to reveal novel genetic targets associated with anthracyclines’ and taxanes’ resistance in breast cancer patients. Materials and methods: We used 125K Affymetrix SNP chip in NCI60 cell line panel treated with the drug of interests to perform genome-wide analysis (GWA) of the polymorphisms associated with resistance to doxorubicin and paclitaxel. Fine mapping of the identified candidate SNPs has been based on Genome Build 36.3. In vitro mRNA expression of the genes in doxorubicin- and paclitaxel resistant cell lines (MCF-7cc, A2780, and MES-SA) have been assessed by quantitative real-time PCR (ABI Prism 7500) and compared by t-test. The biological interactome was constructed on Ingenuity software to recreate the unique interacting pathway within candidate genes implicated in the resistance to both drugs. Results: Using statistical approach previously published by our group, we defined sensitive and resistant cell lines both to doxorubicin and paclitaxel. GWA analyses identified 11 and 48 SNPs associated with doxorubicin and paclitaxel resistance, respectively, after statistical post-hoc adjustment by FDR-BH. Only 16 SNPs were mapped within the well-characterized genes (Doxorubicin: DSG1, FRMD6, RORA, and paclitaxel: ROBO1, SGCD, SNTG1, CCDC26, DCT, BTBD12, ZNF607, GRIK1, CFTR, PLHN2, PTPRD, SLC2A9 and KIAA0427). The mRNA expression analysis showed over-expression of the RORA and DSG1 genes, and under-expression of FRMD6, SGCD, and DCT in resistant cells. Interestingly, three doxorubicin- and six paclitaxel- associated genes were involved in the apoptotic process. ROBO1 is a direct target of p53 gene, whereas DSG1 is directly cleaved by CASP3, the major apoptotic executors. Two genes are participating in the defense mechanism against chemically induced oxidative stress, namely, RORA (as a direct ROS scavenger) and GRIK1 through β-catenin. The constructed interactome showed that there is cross-talk between genes associated with resistance to doxorubicin (directly) and paclitaxel (indirectly, via β-catenin and p53) within oxidative stress and anti-oxidant defense pathway. Conclusion: Genome-wide analysis revealed that genetic variations within apoptotic pathways are correlated with resistance to anthracyclines and paclitaxel. Doxorubicin and paclitaxel share common intracellular targets that define resistance to treatment. Oxidative stress and anti-oxidant defense pathways might serve as pharmacogenomic targets and potential predictive markers for resistance to anthracyclines and taxanes. 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 3586.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".