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Record W2335238283 · doi:10.1158/1538-7445.am2013-63

Abstract 63: Incorporation of flanking probes reduces truncation losses for fluorescence in situ hybridization analysis of recurrent genomic deletions in tumor sections.

2013· article· en· W2335238283 on OpenAlexaff
Maisa Yoshimoto, Olga Ludkovski, Jennifer Good, R. J. Gooding, Jean McGowan‐Jordan, Alexander H. Boag, Andrew Evans, Ming‐Sound Tsao, Paulo Nuin, Jeremy A. Squire

Bibliographic record

VenueCancer Research · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkChildren's Hospital of Eastern OntarioQueen's University
Fundersnot available
KeywordsPTENFluorescence in situ hybridizationBiologyComputational biologyComparative genomic hybridizationDNA microarrayMolecular biologyChromosomeGeneticsCancer researchGeneGene expression

Abstract

fetched live from OpenAlex

Abstract Fluorescence in situ hybridization (FISH) is a robust technique when used with appropriate interpretative guidelines, and the assay can yield consistent results that provide diagnostically and prognostically useful information to help guide patient therapy. The establishment of quality control standards in clinical laboratories using routine FISH analysis of formalin fixed paraffin embedded (FFPE) sections in different tumor types for fusion and break-apart strategies and gene amplifications have been developed for both analysis and reporting, but at the present time there are no comprehensive guidelines for the analysis of genomic deletions using FFPE sections. The use of FISH on archival FFPE samples is technically demanding and becomes more challenging when applied to paraffin-embedded tissue microarrays. The evaluation of FISH signals in interphase nuclei of FFPE sections is affected by truncation and overlapping of the nuclei due to varying cell density, tissue architecture differences and histological forms. In this study we report a generalizable four-color deletion FISH approach to assist interpretation problems arising when evaluating FISH signals. The guidelines will help address interpretative dilemmas associated with overlapping and truncated nuclei in FFPE prostate cancer sections. The four-color FISH approach was developed using the PTEN tumor suppressor gene deletion model in prostate cancer. The PTEN assay was based on a robust bioinformatics analysis of 311 published human genome array datasets and comprises a centromeric “chromosome enumeration” probe, a specific PTEN gene probe, and control flanking probes either side of the target probe. The sensitivity and specificity parameters of the four-color PTEN probe set were further characterized using a large number of well-characterized tumors and stringent scoring criteria. The incorporation of flanking control probes allowed the analysts to determine if the chromosomal region was subject to truncation loss. A minimum threshold for apparent deletion frequency was set to address the heterogeneous and homogeneous nature of tumor histology. In addition the approach facilitated analysis of genotypic heterogeneity and varying clonality within different foci of tumor in the prostate. Overall the approach provided robust and highly reproducible results that minimized inter- and intra-assay variability. The four-color FISH deletion assay reduced the frequency of misinterpretation and improved both the quality and throughput of FISH analyses using clinical samples. Moreover the use of established controls and conservative cut-offs for assigning deletions will facilitate more coherent approach to developing reporting standards for deletion assays as more tumor suppressor genes of clinical importance are discovered by next generation sequencing methods. Citation Format: Maisa Yoshimoto, Olga Ludkovski, Jennifer Good, Robert J. Gooding, Jean McGowan-Jordan, Alexander Boag, Andrew Evans, Ming-Sound Tsao, Paulo Nuin, Jeremy A. Squire. Incorporation of flanking probes reduces truncation losses for fluorescence in situ hybridization analysis of recurrent genomic deletions in tumor sections. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 63. doi:10.1158/1538-7445.AM2013-63

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.041
GPT teacher head0.378
Teacher spread0.337 · 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 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

Citations3
Published2013
Admission routes1
Has abstractyes

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