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Record W4382134319 · doi:10.1186/s12967-023-04242-z

Novel method for highly multiplexed gene expression profiling of circulating tumor cells (CTCs) captured from the blood of women with metastatic breast cancer

2023· article· en· W4382134319 on OpenAlexaff
Morvarid Farhang Ghahremani, Kelly Seto, Woohyun Cho, Michael Craig Miller, Paul W. Smith, David Englert

Bibliographic record

VenueJournal of Translational Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsAptose Biosciences (Canada)
FundersANGLECleveland Clinic
KeywordsCirculating tumor cellBreast cancerMetastatic breast cancerGene expression profilingProfiling (computer programming)MedicineGene expressionCancer researchOncologyGeneCancerInternal medicineMetastasisBiologyComputer scienceGenetics

Abstract

fetched live from OpenAlex

Abstract Background Enumeration of circulating tumor cells (CTCs) has proven clinical significance for monitoring patients with metastatic cancers. Multiplexed gene expression profiling of CTCs is a potential tool for assessing disease status and monitoring treatment response. The Parsortix ® technology enables the capture and harvest of CTCs from blood based on cell size and deformability. The HyCEAD ™ (Hybrid Capture Enrichment Amplification and Detection) assay enables simultaneous amplification of short amplicons for up to 100 mRNA targets, and the Ziplex ™ instrument quantifies the amplicons for highly sensitive gene expression profiling down to single cell levels. The aim of the study was to functionally assess this system. Methods The HyCEAD/Ziplex platform was used to quantify the expression levels for 72 genes using as little as 20 pg of total RNA or a single cultured tumor cell. Assay performance was evaluated using cells or total RNA spiked into Parsortix harvests of healthy donor blood. The assay was also evaluated using total RNA obtained from Parsortix harvests of blood from metastatic breast cancer (MBC) patients or healthy volunteers (HVs). Results Using genes with low expression in WBC RNA and/or in unspiked Parsortix harvests from HVs, the assay distinguished between the different breast cancer and ovarian cancer cell lines with as little as 20 pg of total RNA (equivalent to a single cell) in the presence of 1 ng of WBC RNA. Single cultured cells spiked into Parsortix harvests from 10 mL of HV blood were also detected and distinguished from each other. CVs from repeatability experiments were less than 20%. Hierarchical clustering of clinical samples differentiated most MBC patients from HVs. Conclusion HyCEAD/Ziplex provided sensitive quantification of expression of 72 genes from 20 pg of total RNA from cultured tumor cell lines or from single cultured tumor cells spiked into lysates from Parsortix harvests of HV blood. The HyCEAD/Ziplex platform enables the quantification of selected genes in the presence of residual nucleated blood cells in Parsortix harvests. The HyCEAD/Ziplex platform is an effective tool for multiplexed molecular characterization of mRNA in small numbers of tumor cells harvested from blood.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.040
GPT teacher head0.320
Teacher spread0.280 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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