The 17-Gene Leukemic Stemess Score Can Predict Treatment Outcomes Following Allogeneic Hematopoietic Stem Cell Transplantation in Acute Myeloid Leukemia
Bibliographic record
Abstract
Introduction: A 17-gene stemness score (LSC17 score) had been reported to determine the risk of therapy resistance in acute myeloid leukemia (Nature 2016), and this was replicated successfully in 5 independent cohorts (n=908). When the patients were stratified according to the median value of the LSC17 score, allogeneic hematopoietic stem cell transplantation (HCT) did not affect overall survival (OS) from initial diagnosis for either high- or low-score patients (p=0.2 for high and p=0.06 for low LSC17 score groups). In the present study, we aimed to further perform a subgroup analysis confined to the patients receiving allogeneic HCT and determine whether the LSC17 score at leukemia diagnosis was associated with treatment outcomes including OS, leukemia-free survival (LFS), non-relapse mortality (NRM), relapse incidence (RI), and acute/chronic GVHD following allogeneic HCT. Methods and patients: Out of 452 patients with available LSC17 scores, 123 patients were included into the final analysis who received allogeneic HCT using matched (n=104, 84.6%) or mismatched/haploidentical donors (n=19, 15.4%). 80 patients were from the previous study (Nature 2016), while 43 patients were a prospectively accrued cohort during 2016-2018. Patients and transplant characteristics were: male/female (n=61/62); median age, 51 (17-73); CR status prior to HCT, CR1 (n=93, 75.6%), CR2 (n=30, 24.4%); Conditioning regimen, reduced intensity/myeloablative conditioning (n=59, 48.0% vs n=64, 52.0%); GVHD prophylaxis using post-transplant cyclophosphamide (PTCy; n=45, 36.6%) or T cell depletion (n=62, 50.4%); Cytogenetic risk, favorable (n=10, 8.1%), intermediate (n=70, 56.9%), adverse (n=26, 21.1%), inconclusive or not done (n=17, 13.8%). The LSC17 score for each patient was measured in a diagnostic sample using a NanoString assay and compared to the high/low threshold of a reference AML cohort (Ng et al, Nature 2016 and unpublished data). Transplant outcomes were compared according to the LSC17 risk group for OS, LFS, NRM and RI. Univariate and multivariate analyses were conducted for OS and LFS using Cox's proportional hazard model or for NRM and RI using Fine-Gray model, respectively. The following variables were included in the model: the LSC17 score group (high vs low LSC17 score), chronic GVHD, CR status (CR2 vs CR1), Cytogenetic risk (adverse vs favorable/intermediate/inconclusive), GVHD prophylaxis (PTCy vs others, T-cell depletion vs others), Age (above 60 vs others), donor type (mismatched/haploidentical vs matched donors). Results: With a median follow-up duration of 22 months among survivors after HCT, 23 patients experienced relapse (n=23, 18.7%) while 63 deaths (51.2%) were noted. Out of 123 patients, 58 (47.1%) had a low LSC17 score and 65 (52.9%) had a high LSC17 score. There was no difference in the distribution of LSC17 scores between the group who received HCT (n=123; 0.479±0.026) vs not (n=229; 0.456±0.019; p=0.491). LFS survival was significantly better in the low LSC17 score group (51.5 vs 32.4% for 2-year LFS rate, p=0.0219), and there was a trend to higher OS rate in the low LSC17 group (48.1%) compared to the high LSC17 group at 2 years (34.2%, p=0.09). Furthermore, patients with a low LSC17 score had a significantly lower RI (14.9% vs 27.3% for 2-year relapse incidence, p=0.028). There is no difference of NRM between the groups (37.2% vs 38.2% at 2 years, p=0.647). Multivariate analysis confirmed that the high LSC17 score group was associated with worse LFS (HR 1.874 [1.080-3.249], p=0.025). However, it was not confirmed with respect to OS or relapse incidence. As expected, it was not associated with NRM. Conclusion: A low 17-gene stemness score is associated with better leukemia-free survival and lower relapse incidence after allogeneic HCT, and is suggested to be associated with OS. The high LSC17 score group may be considered for novel therapeutic strategies to reduce the risk of relapse after allogeneic HCT. Figure Disclosures Chan: Celgene: Honoraria, Research Funding; AbbVie Pharmaceuticals: Research Funding; Agios: Honoraria. Minden:Trillium Therapetuics: Other: licensing agreement. Michelis:CSL Behring: Other: Financial Support. Mattsson:Gilead: Honoraria; Celgene: Honoraria; Therakos: Honoraria. Wang:Pfizer AG Switzerland: Honoraria, Other: Travel and accommodation; Pfizer International: Honoraria, Other: Travel and accommodation; Trilium therapeutics: Other: licensing agreement, Research Funding; NanoString: Other: Travel and accommodation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".