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Record W4391837915 · doi:10.3389/fmedt.2024.1360510

Multiplex electrochemical sensing platforms for the detection of breast cancer biomarkers

2024· article· en· W4391837915 on OpenAlexafffund
Connor O’Brien, Chun Keat Khor, Sina Ardalan, Anna Ignaszak

Bibliographic record

VenueFrontiers in Medical Technology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsUniversity of New BrunswickMemorial University of Newfoundland
FundersNew Brunswick Innovation FoundationFondation de la recherche en santé du Nouveau-Brunswick
KeywordsMultiplexBioanalysisBreast cancerDetection limitmicroRNAMultiplex polymerase chain reactionCancerMedicineChromatographyMolecular biologyChemistryNanotechnologyBiologyInternal medicineMaterials scienceBioinformaticsBiochemistryGenePolymerase chain reaction

Abstract

fetched live from OpenAlex

Herein, advancements in electroanalytical devices for the simultaneous detection of diverse breast cancer (BC) markers are demonstrated. This article identifies several important areas of exploration for electrochemical diagnostics and highlights important factors that are pivotal for the successful deployment of novel bioanalytical devices. We have highlighted that the limits of detection (LOD) reported for the multiplex electrochemical biosensor can surpass the sensitivity displayed by current clinical standards such as ELISA, FISH, and PCR. HER-2; a breast cancer marker characterised by increased metastatic potential, more aggressive development, and poor clinical outcomes; can be sensed with a LOD of 0.5 ng/ml using electrochemical multiplex platforms, which falls within the range of that measured by ELISA (from picogram/ml to nanogram/ml). Electrochemical multiplex biosensors are reported with detection limits of 0.53 ng/ml and 0.21 U/ml for MUC-1 and CA 15-3, respectively, or 5.8 × 10 −3 U/ml for CA 15-3 alone. The sensitivity of electrochemical assays is improved when compared to conventional analysis of MUC-1 protein which is detected at 11–12 ng/ml, and ≤30 U/ml for CA 15-3 in the current clinical blood tests. The LOD for micro-ribonucleic acid (miRNA) biomarkers analyzed by electrochemical multiplex assays were all notedly superior at 9.79 × 10 −16 M, 3.58 × 10 −15 M, and 2.54 × 10 −16 M for miRNA-155, miRNA-21, and miRNA-16, respectively. The dogma in miRNA testing is the qRT-PCR method, which reports ranges in the ng/ml level for the same miRNAs. Breast cancer exosomes, which are being explored as a new frontier of biosensing, have been detected electrochemically with an LOD of 10 3 –10 8 particles/mL and can exceed detection limits seen by the tracking and analysis of nanoparticles (∼ 10 7 particles/ml), flow cytometry, Western blotting and ELISA, etc. A range of concentration at 78–5,000 pg/ml for RANKL and 16–1,000 pg/ml for TNF is reported for ELISA assay while LOD values of 2.6 and 3.0 pg/ml for RANKL and TNF, respectively, are demonstrated by the electrochemical dual immunoassay platform. Finally, EGFR and VEGF markers can be quantified at much lower concentrations (0.01 and 0.005 pg/ml for EGFR and VEGF, respectively) as compared to their ELISA assays (EGRF at 0.31–20 ng/ml and VEGF at 31.3–2,000 pg/ml). In this study we hope to answer several questions: (1) Are the limits of detection (LODs) reported for multiplex electrochemical biosensors of clinical relevance and how do they compare to well-established methods like ELISA, FISH, or PCR? (2) Can a single sensor electrode be used for the detection of multiple markers from one blood drop? (3) What mechanism of electrochemical biosensing is the most promising, and what technological advancements are needed to utilize these devices for multiplex POC detection? (4) Can nanotechnology advance the sensitive and selective diagnostics of multiple BC biomarkers? (5) Are there preferred receptors (antibody, nucleic acid or their combinations) and preferred biosensor designs (complementary methods, sandwich-type protocols, antibody/aptamer concept, label-free protocol)? (6) Why are we still without FDA-approved electrochemical multiplex devices for BC screening?

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)0.000
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: none
Teacher disagreement score0.801
Threshold uncertainty score0.392

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.005
GPT teacher head0.270
Teacher spread0.265 · 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

Citations25
Published2024
Admission routes2
Has abstractyes

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