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Record W2991203221 · doi:10.1182/blood-2019-123678

Genome and Exome-Wide Studies Reveal Potential Predictive Efficacy Markers for Venetoclax and Rituximab (VenR) in Relapsed/Refractory Chronic Lymphocytic Leukemia (R/R CLL): Subgroup Analyses of the Murano Trial

2019· article· en· W2991203221 on OpenAlexaff
Arnon P. Kater, Jenny Wu, Julie Dubois, Christopher R. Bolen, Zoe J. Assaf, Peter Hillmen, Barbara Eichhorst, E.F. Eldering, Thomas J. Kipps, Anton W. Langerak, Clemens Mellink, Anne-Marie Van Der Kevie-Kersemaekers, Carolyn Owen, Brenda Chyla, Elizabeth A. Punnoose, Jue Wang, Marcus Lefebure, Michelle Boyer, Kathryn Humphrey, Yanwen Jiang, John F. Seymour

Bibliographic record

VenueBlood · 2019
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsVenetoclaxRituximabMedicineChronic lymphocytic leukemiaOncologyInternal medicineRefractory (planetary science)ExomeAlemtuzumabExome sequencingLeukemiaImmunologyLymphomaAntibodyBiologyGeneticsMutationGene

Abstract

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The first two authors contributed equally. Introduction: VenR (2 years of Ven, plus R during the first 6 months) improved progression-free/overall survival (PFS/OS) vs bendamustine + R (BR) in patients (pts) in with R/R CLL in MURANO (Seymour et al. N Eng J Med 2018). MURANO also showed early, sustained and durable undetectable minimal residual disease (uMRD) status with VenR, which is associated with prolonged survival in CLL (Kater et al. J Clin Oncol 2019). Here we explore associations between baseline molecular characteristics and VenR-induced MRD responses and PFS based on the 4-year follow-up of MURANO. Methods: DNA specimens from CD19-enriched baseline samples (313/389 enrolled pts) were analyzed with whole-exome sequencing (WES). Genetic complexity (GC) was assessed by array comparative-genomic hybridization. Gene expression data were generated by RNA sequencing from matched RNA samples (209 pts). Univariate analysis determined the impact of gene mutations, GC, and BCL-2 (family) expression on MRD and PFS at end of combination therapy (EOCT) and end of treatment (EOT). MRD (peripheral blood only) was categorized as uMRD <1 CLL cell/10,000 leukocytes (<10-4), low MRD (≥10-4 to <10-2) or high MRD (≥10-2). Array-based GC status was non-complex = 0-2, low GC = 3-4 and high GC = ≥5 aberrations. Results: Mutation frequencies/GC status at baseline were equally distributed between arms. All 313 pts had CLL cells with non-silent, deleterious mutations by WES (mean 47/pt; 0.97±0.3 mutations/megabase). Of 44 frequently mutated genes, 202/313 (65%) pts had ≥1 frequent mutation; 69/313 (22%) pts had ≥2. Frequencies (%) of deleterious mutations were TP53 21.7, ATM 18.8, NOTCH1 17.9, SF3B1 12.5, XPO1 9.9, BIRC3/POT1/BRAF/EGR2 5.1-5.4, rest <5%; ELF4, HISTIH1B, MED12 or PIM1 = 0. Deleterious gene mutations were more frequent in CLL pts with unmutated (91.9%) vs mutated (65.5%) IGHV (p=0.08). Of 288 pts with GC data, 113 (39.2%) = non-complex, 64 (22.2%) = low GC and 27 (9.4%) = high GC. Further in-text analyses refer to VenR only. WES data: BIRC3 mut and BRAF mut tended to be enriched in pts with detectable MRD at EOCT (% MRD+ in mutation vs wild type: 62.5% vs 23.7% [p=0.146] and 55.6% vs 21.4% [p=0.027] respectively) (Table 1). At EOT, NOTCH1 mut and TP53 mut were negatively associated with uMRD (35.3% vs 63.5% [p=0.10]; 41.7% vs 63.9% [p=0.028]) (Table 1). These observations were concordant with observed PFS outcomes (Figure 1). Array data: Negative effects on MRD status were seen in pts with either del17p at EOCT (p=0.055) and at EOT (p=0.054) or del13q14bi at EOCT (p=0.018) (Table 1). Trends were seen for gain 2p, loss 18p/4q/trisomy 12 at EOCT and gain 2p/8q, loss 14q/18p/4q and trisomy 12 at EOT. High MRD+ at EOT was also associated with low and high GC vs non-complex GC (p=0.042) (Figure 2). PFS was shorter in high but not low GC pts at 36-mo follow-up (HR 3.2, p=0.0055; HR 1.1, p=0.77). Conversely, after 4-years follow-up, low GC pts had reduced PFS benefit vs non-complex GC (HR 2.0, p=0.025; Figure 3), differing from previously reported findings (Lugano, 3-year follow-up). The delayed deterioration in PFS benefit in low GC pts was unprecedented, and warrants further investigation into prognostic risks associated with this subgroup. RNA expression data: Gene-specific and pathway-level enrichment analyses are ongoing to explore associations between RNA sequencing data and MRD status. Preliminary gene expression analyses showed that pts with MRD+ at EOCT expressed higher BCL-2 than those with uMRD (p=0.028), but not at EOT (Table 1). There was a trend towards increased MCL-1 expression from high MRD to low MRD and uMRD at EOT. Conclusions: We identified genomic alterations having impact on MRD response at EOCT and EOT (i.e. BIRC3, BRAF, NOTCH1, TP53): mutations mostly were associated with increased MRD and del17p tended to lead to increase in high and low clones of MRD+. Low/high GC negatively impacted long-term PFS with VenR and may represent high-risk pt subgroups. High BCL-2 may associate with MRD+ at EOCT but not at EOT. Given the small size of the genomic alteration cohort, further validation of these findings are needed. Studying the large CLL clinicogenomic data in MURANO helped determine whether VenR combinations overcome challenges posed by CLL/SLL with unfavorable clinical characteristics, and further identify biomarkers that may predict clinical benefits in these pts. Disclosures Kater: AbbVie: Consultancy, Honoraria, Research Funding; Roche: Other: Travel funding, Research Funding; Genentech: Research Funding. Wu:Genentech, Inc.: Employment, Equity Ownership. Bolen:F. Hoffmann-La Roche: Equity Ownership; Genentech, Inc.: Employment. Assaf:Genentech, Inc.: Employment, Equity Ownership. Hillmen:AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Expenses, Research Funding; Acerta: Membership on an entity's Board of Directors or advisory committees; Apellis: Research Funding; Gilead: Research Funding; Roche: Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Expenses, Research Funding. Eichhorst:AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; ArQule: Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BeiGene: Research Funding; Gilead Sciences, Inc.: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Eldering:Genetech, Roche, AbbVie: Research Funding. Kipps:AstraZeneca, Inc.: Membership on an entity's Board of Directors or advisory committees; Verastem: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Jannsen Pharmaceutical Companies of Johnson & Johnson: Honoraria, Membership on an entity's Board of Directors or advisory committees; Genentech, Inc.: Membership on an entity's Board of Directors or advisory committees, Research Funding; Velos-Bio: Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Research Funding. Langerak:Gilead: Research Funding, Speakers Bureau; Janssen: Speakers Bureau; F. Hoffmann-La Roche Ltd: Research Funding; Genentech, Inc.: Research Funding. Mellink:Roche/Genentech: Research Funding. Van Der Kevie-Kersemaekers:Array analysis is financed by Roche/Genentech: Research Funding. Owen:AstraZeneca: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Roche: Honoraria, Research Funding; Gilead: Honoraria, Research Funding; Teva: Honoraria; Merck: Honoraria; Acerta: Research Funding. Chyla:Abbvie, Inc: Employment, Other: Stock or options. Punnoose:Roche: Other: Stock/stock options; Genentech, Inc.: Employment. Wang:Roche: Equity Ownership; Genentech, Inc.: Employment. Lefebure:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership. Boyer:F. Hoffmann-La Roche Ltd: Employment. Humphrey:F. Hoffmann-La Roche Ltd: Employment. Jiang:Genentech: Employment, Equity Ownership; F. Hoffman-La Roche: Equity Ownership. Seymour:Roche: Consultancy, Research Funding, Speakers Bureau; Janssen: Consultancy, Research Funding; Acerta: Consultancy; AbbVie: Consultancy, Honoraria, Research Funding, Speakers Bureau; Celgene: Consultancy, Research Funding, Speakers Bureau; Takeda: Consultancy.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.379
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.028
GPT teacher head0.319
Teacher spread0.291 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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".

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Citations1
Published2019
Admission routes1
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