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Record W2040850710 · doi:10.1373/clinchem.2005.064972

Validation of Breast Cancer Biomarkers Identified by Mass Spectrometry

2006· letter· en· W2040850710 on OpenAlexaff
Eleftherios P. Diamandis

Bibliographic record

VenueClinical Chemistry · 2006
Typeletter
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsBreast cancerMass spectrometrySurface-enhanced laser desorption/ionizationCancerMedicineChromatographyOncologyChemistryInternal medicineTandem mass spectrometryProtein mass spectrometry

Abstract

fetched live from OpenAlex

Li et al. (1) should be congratulated for a valiant effort to validate 3 previously identified serum breast cancer biomarkers by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). Because there is considerable controversy on the value of this technology for cancer diagnostics (2)(3)(4)(5)(6)(7)(8)(9)(10)(11), it is important to comment on validation studies aiming to reproduce previously published data. Among 3 previously reported biomarkers, BC1, BC2, and BC3, one of these (BC1) was not confirmed, as it was previously shown to be decreased in breast cancer, whereas in the validation study by Li et al. (1), it was increased. The other 2 candidate biomarkers, BC2 and BC3, were positively identified, by tandem MS, as complement C3a lacking its C-terminal arginine (C3adesArg). BC2 was also identified as a truncated form of C3adesArg. In my opinion, the data presented in Fig. 4 of the article by Li et al. (1), showing the relative intensities of BC2 and BC3 in various groups of patients, are rather disappointing. For BC2, there is no difference between patients with benign breast diseases and patients with invasive carcinomas, although an increase was seen in ductal carcinoma in situ (DCIS). For BC3, there was no difference among patients with benign disease, DCIS, or invasive carcinomas. The remaining question concerns the possible value of complement C3adesArg and its fragment as candidate breast cancer biomarkers. The data provided by the authors (1) confirm my previous predictions that SELDI-TOF–identified biomarkers represent high-abundance proteins (in this case, C3, present in serum at concentrations of ∼1.2 g/L) that are produced mostly by the liver (3)(4)(5)(6). The proteolytic processing of peptides in the circulation by amino- and carboxypeptidases is well known, and it should not be surprising that the identified molecules represent modified and/or truncated forms of C3a. I have previously speculated that a large number of SELDI-TOF–identified candidate biomarkers are acute-phase reactants (3)(4)(5)(6). C3, in accordance with my previous predictions, is also an acute-phase reactant whose serum concentration is increased or decreased in a wide variety of clinical conditions (12). I conclude that the positive identification of previously described candidate serum biomarkers, BC2 and BC3, confirms my previous predictions that these are high-abundance proteins produced by the liver and that they represent nonspecific biomarkers of acute-phase reaction. Their performance as breast cancer biomarkers, as assessed by SELDI immunoassay, is not impressive and likely of questionable clinical value.

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)0.006
metaresearch head score (Gemma)0.016
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0010.003

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 head0.020
GPT teacher head0.322
Teacher spread0.302 · 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

Citations16
Published2006
Admission routes1
Has abstractyes

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