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Abstract P2-01-05: Comprehensive analysis of genomic alterations in tumor tissue associated with presence of various subpopulations of circulating tumor cells (CTCs) in primary breast cancer

2018· article· en· W2790039224 on OpenAlexaff
Michal Mego, Tomáš Tokár, Gabriel Minárik, Magdalena Hajduk, Marián Karaba, Juraj Benca, Tatiana Sedláčková, Gabriela Repiská, Lucia Krasničanová, Ján Macúch, Gabriela Sieberova, Daniel Pinďák, Massimo Cristofanilli, JM Reuben, Igor Jurišica, Jozef Mardiak

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsCirculating tumor cellBreast cancerCancer researchmicroRNAGeneCancerPrimary tumorBiologyEpithelial–mesenchymal transitionMetastasisGenetics

Abstract

fetched live from OpenAlex

Abstract Background: CTCs play a major role in tumor dissemination and progression, and represent one of the key components of the metastatic cascade. The aim of this study was to identify signaling pathways associated with presence of CTCs in primary breast cancer (PBC) patients using a comprehensive genomics approach. Methods: This translational study included 78 patients with PBC. CTCs were detected before surgery by quantitative RT-PCR assay for expression of epithelial (EP; CK19) or epithelial-mesenchymal transition (EMT) genes (TWIST1, SNAIL1, SLUG, ZEB1). Total DNA and RNA were extracted, in parallel, from fresh frozen primary tumor and the microRNA and mRNA expression profiles were obtained using Human microRNA Microarray v21.0 and SurePrint G3 Human Gene Expression v3 (Agilent Technologies). Next generation sequencing (NGS) was performed by Illumina Multiplex Sequencing using MiSeq Sequencing Reagent Kit V3. Results:Mutations in BRCA1/2 genes in tumor tissue were more common in patients with epithelial CTCs (CTC_EP) compared to patients without epithelial CTCs in peripheral blood (23.5% vs. 0%, p = 0.02), while there were no mutations in specific genes associated with CTC with EMT phenotype (CTC_EMT).Further, we identified 90 genes and 7 miRs that were expressed at significantly different levels in tumors with presence of CTC_EP and 199 genes and 13 miRs specifically associated with CTC_EMT, compared to tumors with non-detectable CTCs. We also identified 39 overlapping genes and 7 miRs, that were expressed at significantly different levels in tumors with CTC_EP and/or CTC_EMT compared to tumors with non-detectable CTCs. Overlapping genes and miRs with highest different levels in expression were ATAD3A, TMEM201, DCPS, DOCK9-AS2, TRAF2 and miR-5195-3p, miR-188-5p, miR-6780a-5p, miR-6757-5p. Signalling pathways associated with these genomic alterations belong to several critically functional groups, such as immune response, signal transduction, cell proliferation, cell cycle progression, or apoptosis were significantly differentially based on CTCs status. Conclusions: We identified for the first time various genomic alterations in primary tumor tissue of PBC associated with different CTCs subpopulations in peripheral blood. We hypothesize that these genomic alterations could play a role in tumor dissemination and progression and might lead to identification of new therapeutic targets. Citation Format: Mego M, Tokar T, Minarik G, Hajduk M, Karaba M, Benca J, Sedlackova T, Repiska G, Krasnicanova L, Macuch J, Sieberova G, Pindak D, Cristofanilli M, Reuben JM, Jurisica I, Mardiak J. Comprehensive analysis of genomic alterations in tumor tissue associated with presence of various subpopulations of circulating tumor cells (CTCs) in primary breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-01-05.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.064
GPT teacher head0.384
Teacher spread0.320 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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