A Gene Expression Signature in Diagnostic Formalin Fixed Paraffin Embedded Tissue Predicts Overall Survival in Locally Advanced and Advanced Stage Classical Hodgkin Lymphoma – a Correlative Study From the E2496 Intergroup Trial
Bibliographic record
Abstract
Abstract Abstract 430 Introduction: 25–30% of patients with advanced stage classical Hodgkin lymphoma (cHL) develop progressive disease despite treatment with ABVD. While more intensive upfront treatments, such as BEACOPP, result in a higher failure free survival, this comes at the expense of increased toxicity and morbidity. 10–15% of patients with advanced stage cHL will ultimately succumb to the disease, with similar outcomes using different upfront regimens likely reflecting the planned use of second-line high dose therapy. The International Prognostic Factors Project Score, a prognostic tool developed using freedom from progression of disease as the outcome, has been used in clinical practice and has guided clinical trials. We hypothesized that biological factors, as measured by gene expression profiling in pretreatment formalin fixed paraffin embedded tissue (FFPET) samples, might provide a robust predictor of overall survival (OS). Method and Patients: NanoString technology was used to quantitate 261 mRNA species in diagnostic FFPET samples from patients in the Intergroup E2496 trial, which compares ABVD with Stanford V chemotherapy in locally advanced and advanced stage cHL. The 261 genes included individual genes and genes that represent cell and cellular process signatures that have been associated with outcome in cHL. Total RNA was extracted from whole section scrolls from the 309 FFPET blocks available. A penalized binary logistic regression model with leave-one-out cross validation was used to produce a parsimonious predictive model for OS. A threshold was selected that maximized the Chi square of the Log Rank (Mantel-Cox) test between the identified low and high risk groups. An independent cohort of patients with advanced stage cHL enriched for treatment failure, consisting of 59 patients from British Columbia treated with ABVD and 71 patients from Portugal treated with Stanford V, was used to test the generated model and threshold. Results: Gene expression of adequate quality was produced in 293 of the 309 samples (95%). At a median follow up of 5.3 years, 36 (12%) of the 293 patients had died. 51 genes were differentially expressed (t-test p < 0.05) with respect to OS, including genes that are part of macrophage, cytotoxic/NK cell and apoptosis signatures. A predictive model for OS was produced with an area under the curve (AUC) of the receiver operating characteristic (ROC) curve of 0.73. The predictor identified a high-risk group, comprising 39% of the cohort, with a 77% estimated 5-year OS compared with 96% in the low risk group (Figure 1A, log-rank p < 0.0001). The predictor was validated in the independent cohort giving an AUC of the ROC curve of 0.73 and an estimated 5-year OS of 71% in the high-risk group compared with 91% in the low risk group (Figure 1B, log-rank p = 0.006). Discussion: We have produced a parsimonious gene expression-based predictor of OS in cHL, developed in, and applicable to, widely available FFPET using NanoString technology. The predictor identifies, at diagnosis, a clinically meaningful proportion of patients at significantly higher risk of death when treated with ABVD or Stanford V. Further evaluation of the gene expression signature with alternative treatments, ideally in the context of clinical trials, is needed to understand the impact of more intensive cytotoxic therapies versus novel targeted approaches. Disclosures: Horning: Genentech: Employment, Equity Ownership. Connors:Seattle Genetics: Consultancy, Research Funding.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".