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Enregistrement W2519777424 · doi:10.1182/blood.v126.23.368.368

Evaluation of Circulating Tumour DNA for the Mutational Characterisation of Multiple Myeloma

2015· article· en· W2519777424 sur OpenAlexaff
Andrew Spencer, Sridurga Mithraprabhu, Malarmathy Ramachandran, Daniela Klarica, Jane S. Hocking, Laura Mai, Stephanie J. Walsh, David Broemeling, Andre Marziali, Anna Kalff, Matthew Wiggin, Brian G.M. Durie, Tiffany Khong

Notice bibliographique

RevueBlood · 2015
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensCollège Boréal
Organismes subventionnairesnon disponible
Mots-clésNeuroblastoma RAS viral oncogene homologDigital polymerase chain reactionKRASExomeExome sequencingDNACell-free fetal DNAMolecular biologyLiquid biopsyMultiple myelomaCancer researchBiologyMutationPolymerase chain reactionCancerMedicineGeneticsGeneImmunology

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Whole exome sequencing (WES) of bone marrow (BM) has demonstrated recurring single nucleotide variations in multiple myeloma (MM) with activating mutations (MTS) of the RAS-MAPK pathway identified in 50% of patients. These same data have also demonstrated significant intra-clonal heterogeneity. Based on the technical limitations of BM biopsy in MM we have evaluated the utility of circulating free (tumour derived) DNA (ctDNA) in the plasma of MM patients as a potential target for the mutational characterisation of MM. Methods: Blood (30ml) from MM patients (pts) and normal volunteers (NV) was collected into Streck Cell-Free DNA BCT tubes, centrifuged immediately and DNA extracted using the QIAamp circulating nucleic acid kit (Qiagen). Plasma ctDNA was quantified with a QUBIT Fluorometer and high sensitivity DNA detection kits (Life Technologies). BM aspirates from MM patients were CD138 enriched using the MACS Bead System and DNA extracted (Qiagen). Paired BM CD138 DNA and ctDNA mutational profiles were characterised with the OnTarget™ Mutation Detection (OMD) platform (Boreal Genomics) that includes 42 unique MTS potentially relevant to MM (KRAS n=18, NRAS n=10, TP53 n=8, BRAF n=6). OMD findings were subsequently validated with ddPCR (Biorad QX200 droplet digital PCR system). For WES of ctDNA, library prep and exome capture were undertaken with the NEBNext Ultra Library prep kit (Genesearch) and SureSelect XT2 human exome V5.0 kit (Agilent), respectively. Sequencing was then undertaken on an Illumina HiSeq 2500 and processed via the APF human exome pipeline. Results: Higher quantities of circulating free DNA were obtained from MM pts (n=37) than NV (n=21) (median 23ng/ml [range 5-195ng/ml] versus 15ng/ml [range 6-32ng/ml], respectively, p = 0.009). Twenty-eight MM pts (10 newly diagnosed [ND] and 18 relapsed/refractory [RR]) had contemporaneous CD138 enriched MM tumour cell populations collected and all 28 paired BM MM DNA and ctDNA specimens along with 3 wild-type (WT) DNA controls underwent OMD. A total of 72 MTS (KRAS n=36 [50%], NRAS n=19 [26%], BRAF n=4 [6%], TP53 n=13 [18%]) were detected in the MM pts (BM and/or ctDNA) with none detected in WT controls. More MTS were present in RR pts compared with ND pts - median 2.5 (range, 0-11) versus 1 (range, 0-3), respectively, p=0.03 and all 13 TP53 MTS were found exclusively in RR patients. Twenty-four randomly selected OMD low-level positive or negative samples (but with an identified MTS in matched BM or ctDNA samples) were studied with mutation-specific ddPCR. Of 11 OMD positive samples 10 (91%) were positive with ddPCR while 3 negative with OMD tested positive with ddPCR. Thirty MTS were found with OMD both in BM and ctDNA, 23 only in BM and 19 only in ctDNA. Moreover, in 5 of 30 MTS found in BM and ctDNA the mutational load (mutational allele frequency versus WT allele frequency) was proportionately greater within the ctDNA, thus a total of 24 MTS (33%) were detected with OMD, exclusively or predominantly, distant to the BM biopsy site. Activating MTS of the RAS-MAPK pathway (KRAS/NRAS/BRAF) were detected (BM and/or ctDNA) in 22 of 28 pts (79%) comprising 90% of ND pts (median MTS 1, range 0-3) and 72% of RR pts (median MTS 1, range 0-11), moreover, 8 of 18 (44%) RR pts harboured ≥2 activating MTS (2, 2, 3, 4, 4, 8, 8, 11 each). Exploratory WES was undertaken on 4 ctDNA samples and demonstrated predominantly exonic variants of 108, 152, 101 and 98 distinct genes with median read depths of 115, 79, 78 and 65, respectively. Variants were enriched for C>T transitions (51%, 45%, 51% and 44% of all variants, respectively) reflecting spontaneous deamination of methylated cytosine to thymine as has been described with WES of MM BM. Conclusions: Our data confirm the utility of ctDNA evaluation as an adjunct to the mutational characterization of MM. Furthermore, using highly sensitive targeted approaches we have demonstrated a more complex mutational landscape in MM than previously shown with BM WES. In our cohort, activating MTS of the RAS-MAPK pathway were highly prevalent with our findings suggesting a striking subclonal convergence on this pathway. We conclude that high-sensitivity approaches incorporating plasma ctDNA evaluation aimed at identifying actionable MTS may represent a significant advance in attempts to personalize future MM treatment strategies and that future studies incorporating RAS-MAPK pathway targeted approaches for MM are essential. Disclosures Mai: Boreal Genomics: Employment. Walsh:Boreal Genomics: Employment. Broemeling:Boreal Genomics: Employment. Marziali:Boreal Genomics: Employment. Wiggin:Boreal Genomics: Employment.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,009

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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.

Tête enseignante Opus0,127
Tête enseignante GPT0,362
Écart entre enseignants0,235 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2015
Routes d'admission1
Résumé présentoui

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