Validation of a custom 512-gene breast cancer panel on the illumina-based DASL mRNA expression platform: focus on triple negative breast tumors using RNA from stored formalin-fixed, paraffin blocks.
Bibliographic record
Abstract
Abstract Abstract #2027 Background: DASL (cDNA-mediated Annealing, Selection, extension Ligation) is a recently described, RT-PCR-based, multiplex gene expression assay developed by Illumina specifically for use with fragmented RNA prepared from formalin-fixed paraffin-embedded (FFPE) samples. For use with this assay, we have designed a custom 512-gene breast cancer panel, validated this panel with FFPE breast tumor samples, and identified novel genes associated with the triple negative (TN) subtype. Material and Methods: The DASL assay was used to measure mRNA levels from RNA isolated from 5 um FFPE breast tumor sections using the Roche High Pure Kit. Samples that passed our quality control tests were run in the assay. Arrays were imaged using a BeadArray Reader and data was analyzed using BeadStudio software. Differential mRNA regulation was identified by Significance Analysis of Microarrays software using a false discover rate (q-value < 0.01) or Bonferroni correction of the two-tailed Student's t-test. IHC concordance was measured by mRNA expression fold-change for positive versus negative IHC categories. Results: To validate our custom breast cancer panel, we performed the DASL assay on 187 samples from 87 patients with differing receptor status as previously determined by IHC (ER, PR, HER2) and/or FISH (HER2). Correlation between 152 common genes on Illumina's 502-gene standard cancer panel and our custom panel was very high; R2 value of 0.88. Concordance between IHC/FISH and DASL data for ESR1, PGR and ERBB2 was > 90%. We identified 73 genes differentially expressed between TN and the other tumor samples. Of these, 20 were in common between the standard and custom panels, 53 were uniquely expressed on the custom panel. These included genes associated with the TN/Basal subtype identified in previous microarray studies; CXCL1, CDH3, ANXA8, KRT5, TRIM29, KRT17, MFGE8, CX3CL1, FZD7, CHI3L2, B3GNT5 (PNAS 100:8418, 2003) and CDH3, CRABP1, CX3CL1, FOXC1, MMP7 (BMC Genomics 7:96, 2006) further validating both DASL assay and custom panel. In addition, we identified genes not previously linked to the TN subtype, highlighting the potential utility of the custom panel for profiling breast tumor FFPE specimens in the DASL assay. Discussion: We have designed and validated a custom 512-gene breast cancer panel for expression profiling studies using RNA prepared from FFPE tumor specimens on the DASL platform. Thus far, we have identified a 73-gene set with the custom panel (significantly more genes than with the standard panel) that can discriminate TN from other receptor expressing subtypes. We are now applying this platform to samples from clinical trials in order to identify both prognostic and predictive breast tumor gene sets. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 2027.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".