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Record W2899267864 · doi:10.1182/blood-2018-99-118617

Analysis of Sequential Patient Samples from the Mmrf Commpass Study Identifies a High Risk Progression Phenotype

2018· article· en· W2899267864 on OpenAlexaboutno aff
Sheri Skerget, Daniel Peñaherrera, Jessica Aldrich, Sara Nasser, Austin Christofferson, Christophe Legendre, Martin Boateng, Lori Cuyugan, Jonathan Adkins, Erica E. Tassone, Jennifer Yesil, Daniel Auclair, Winnie S. Liang, Sagar Lonial, Jonathan J. Keats

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsNeuroblastoma RAS viral oncogene homologKRASMultiple myelomaOncologyInternal medicineExomeMedicineMalignancyExome sequencingMutationCancerBiologyGeneticsGeneColorectal cancer

Abstract

fetched live from OpenAlex

Abstract Multiple myeloma (MM) is a hematological malignancy of plasma cells accounting for ~2% of new cancer cases each year in the United States. The Multiple Myeloma Research Foundation CoMMpass Study (NCT01454297) is a fully accrued, longitudinal, observational clinical trial with 1143 newly diagnosed MM patients from sites in the United States, Canada, Spain, and Italy. Tumor samples are collected and characterized using whole genome (WGS), exome (WES), and RNA (RNAseq) sequencing at diagnosis and each progression event. Clinical parameters are collected at baseline and every three months through the eight-year observation period. Although ongoing, longitudinal collection of molecular and clinical data from CoMMpass patients has aided in our understanding of the molecular mechanisms underpinning relapse in MM. The CoMMpass IA13 dataset includes 136 patients with longitudinal time points, including 25 patients with multiple progression events. We analyzed 100 patients with WES data at baseline and at least one progression event and identified 7 genes (KRAS, NRAS, SPEN, SRCAP, MACF1, ANK3, and RPRD2) with acquired non-synonymous mutations in at least 3% of patients at progression. We identified five patients with KRAS mutations at baseline in whom a clonal shift to NRAS Q61 mutations occurred at progression and four additional patients with novel NRAS Q61 mutations becoming detectable at progression. Patients with NRAS Q61 mutations at baseline exhibit poor OS outcomes as compared to patients with other NRAS mutations (p < 0.05), and exhibit no significant difference in outcome compared to patients with KRAS mutations, suggesting that clones with NRAS Q61 mutations have a competitive advantage over other NRAS mutations in MM. An integrated analysis leveraging WGS, WES, and RNAseq data identified gain- (GOF) and loss-of-function (LOF) genes for each sample. Longitudinal changes in gene functional status was determined for 47 patients with 57 paired time points. TRAF3 and CDKN2C/FAF1 were found to be the most common complete LOF events acquired at progression, found in 5 (10.6%) and 4 (8.5%) patients, respectively. Acquired complete LOF events are enriched for genes involved in cell cycle regulation (15% of patients, p < 0.001), including CDKN1B, CDKN2A, CDKN2C, PPP2R4, TP53, and RB1, indicating that novel events resulting in further destabilization of cell cycle control contribute to relapse in MM. Recurrent GOF events acquired at progression involving KRAS, PEAR1, and CDYL2 were observed in >4% of longitudinal patients. In addition, 5 (10.6%) patients acquired GOF events in genes either up- or downstream of RAS, including HIST2H3C, OSMR, PAK2, PIK3R6, and STAT3, highlighting the complexity of targeting RAS in MM. Unsupervised consensus clustering of RNAseq data for 714 patients at baseline identified 12 expression subtypes of MM, which generally correspond with known subgroups. The proliferation (PR) group consists of patients whose tumors have an array of genetic backgrounds but a similar RNA expression profile, and exhibit poor OS (HR = 3.996, 95% CI = 2.632 - 6.067, p < 0.001) and PFS (HR = 2.583, 95% CI = 1.817 - 3.67, p < 0.001) outcomes. We analyzed 50 patients with RNAseq data at multiple time points and identified 21 (42%) tumors that changed expression subtypes at progression, 12 (24%) of which transition to PR. Patients who transition to PR have extremely poor outcomes, with 75% of patients succumbing to their disease soon after progression (median = 2 months). Tumors with the PR subtype commonly possess del1p, gain1q, del13p, and LOF of RB1 (p < 0.001), and tumors that transition to PR at progression commonly acquire one or more of these abnormalities. Further, 4 (33%) patients that transition to PR acquire complete LOF of a cyclin-dependent kinase inhibitor, with 3 (25%) patients acquiring focal deletions of CDKN2C/FAF1 at progression. Although we observe multiple mechanisms driving the transition to PR, it is seemingly associated with acquired molecular alterations that result in further loss of cell cycle control. These observations suggest that progression in MM is often driven by marked shifts in gene expression and molecular events that further deregulate RAS and cell cycle pathways, highlighting the need for novel inhibitors in MM; protocols, such as MyDRUG, which aim to treat patients based on their tumor genetic profile; and molecular profiling of patients throughout their disease course. Disclosures Lonial: Amgen: Research Funding.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.036
GPT teacher head0.335
Teacher spread0.300 · 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 designObservational
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

Citations2
Published2018
Admission routes1
Has abstractyes

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