Analysis of Sequential Patient Samples from the Mmrf Commpass Study Identifies a High Risk Progression Phenotype
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».