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Record W4280516697 · doi:10.1042/bsr20220040

Commentary on: SMARCB1 as a novel diagnostic and prognostic biomarker for osteosarcoma

2022· article· en· W4280516697 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBioscience Reports · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChromatin Remodeling and Cancer
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of AlbertaUniversity of Ottawa
Fundersnot available
KeywordsSMARCB1BiologyCancer researchBiomarkerGene expressionGeneGeneticsChromatin remodeling

Abstract

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In the last couple of decades, biomarkers have been on the rise for diagnostic and predictive value. There has been a rush to identify new markers using new technologies and drug repurposing approaches. SMARCB1 acronym arises from the SWI/SNF (SWItch/Sucrose Non-Fermentable)-related Matrix-associated Actin-dependent Regulator of Chromatin subfamily B member 1 (SMARCB1). It is a molecule, whose role is associated with the sucrose metabolism. SMARCB1 is also called INI1 (Integrase Interactor 1). The molecule was discovered in the mid-1990s. Its role as a loss-of-function marker for malignant rhabdoid tumors (MRT) of renal and extrarenal origin has enormously expanded the spectrum of involved neoplasms since that time. Several tumors have been characterized by genetic aberrations in the SMARCB1 gene. They include reduction in expression, loss of expression, and mosaic expression. Most of the tumors are sarcomas, but a variegated group of tumors with mixed phenotypes has also been delineated. It is well known that the outcome of patients harboring genetic aberrations in the SMARCB1 gene has been poor. Guo et al. reported that reduced SMARCB1 expression occurred in 70% of osteosarcomas. Their data significantly correlated with poor neoadjuvant response. These authors emphasize a shorter progression-free and overall survival of the patients demonstrating an altered expression of this gene. Interestingly, mRNA in silico analysis established that SMARCB1 expression correlates with the response to chemotherapy of osteosarcoma patients, but there was no reliable correlation between SMARCB1 expression level and metastasis, response to neoadjuvant therapy, overall survival, and progression-free survival. The study involved a tissue microarray (TMA) on bone tumors that may limit the full evaluation of the gene expression. Nevertheless, Guo et al.'s study is remarkable. It expands the list of the tumors harboring an altered SMARCB1 gene expression and suggests that this marker should be investigated in every pathology workup for potential predictive value. On the other side, much work needs to be done if we hope that we strive to provide additional therapeutic strategies for osteosarcoma patients with altered SMARCB1 gene expression.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.752
Threshold uncertainty score0.438

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 integrity0.0000.000
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 head0.017
GPT teacher head0.278
Teacher spread0.261 · 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