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Enregistrement W2912419979 · doi:10.1158/2326-6074.cricimteatiaacr18-b085

Abstract B085: High mutation burden and response to immune checkpoint inhibitors in angiosarcomas of the scalp and face

2019· article· en· W2912419979 sur OpenAlexaboutno aff
Corrie Painter, Esha Jain, Michael Dunphy, Elana Anastasio, Mary McGillicuddy, Rachel Stoddard, Beena Thomas, Sara Balch, Kristin Anderka, Katie Larkin, Niall J. Lennon, Yen‐Lin Chen, Andrew Zimmer, Esme O. Baker, Simone Maiwald, Jen Lapan, Jason L. Hornick, Chandrajit P. Raut, George D. Demetri, Eric S. Lander, Todd R. Golub

Notice bibliographique

RevueCancer Immunology Research · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueVascular Tumors and Angiosarcomas
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineAngiosarcomaInternal medicineExomeExome sequencingOncologyPathologyBiologyMutationGene

Résumé

récupéré en direct d'OpenAlex

Abstract Objective: Angiosarcoma (AS) is a rare soft tissue sarcoma, with an incidence of 300 cases/yr and a 5-year DSS of 30%. The low incidence has impeded large-scale research efforts. To address this, we launched a patient-partnered genomics study which seeks to empower patients to accelerate research by remotely sharing their samples and clinical information. Methods: We developed a website (ASCproject.org) to allow remote acquisition of medical records (MR), saliva, blood, and archival tissue from patients in the US and Canada. Whole-exome sequencing (WES) of ~20,000 genes is performed on tumor and matched germline DNA. Transcriptome analysis is performed on tumor RNA. Ultra-low pass whole-genome sequencing (ULP-WGS) and in some cases WES is performed on cell free DNA (cfDNA) obtained from blood samples. Clinical data including information about demographics, diagnosis, treatments, and responses are obtained via patient-reported data (PRD) and through MR abstraction. The resulting clinically annotated genomic database is shared widely to identify genomic drivers and mechanisms of response and resistance to therapies. Results: Since launch on March 13 2017, 321 patients with AS have registered. The average age of patients is 56 yrs (range 22-89). Primary locations of AS were primary breast (24%), breast with prior radiation (20%), head/face/neck/scalp (HFNS) (21%), bone/limb (9%), abdominal (3%), heart (3%), lung (1%), liver (1%), lymph (0.5%), multiple locations (11%), and other locations (5%). 142 (48%) reported being disease free at the time of enrollment. To date, 153 saliva kits, 167 MRs, 43 blood samples, and 97 tissue samples have been obtained. WES analysis is complete for 14 samples.ULP-WGS is complete for 10 cfDNA samples, and WES on 4 cfDNA samples. Transcriptome sequencing is complete for 9 tumor samples. We identified several previously described genes known to be altered in AS, including recurrent alterations in KDR and TP53. Tumor mutational burden (TMB) and mutational signature activities were quantified for each tumor sample. All three of the AS from the HFNS in the initial cohort exhibited a high TMB (>150 mutations) and dominant UV light signature (COSMIC Signature 7). Based on this, we hypothesized that HFNS AS might respond well to immune checkpoint inhibitors. We identified through PRD 56 patients with HFNS AS who reported what medications they received. Of these, 2 reported receiving immune checkpoint inhibitors for the treatment of metastatic disease. Both patients had refractory metastatic HFNS AS and reported receiving off-label anti-PD1 therapy. Both had complete or near-complete responses following immunotherapy, and currently report having no evidence of disease. Clinical responses were confirmed through review of MRs. Sequencing is currently being performed on tumor samples from both patients. Conclusion: A patient-partnered approach enabled rapid identification and enrollment of over 300 patients with AS, an exceedingly rare cancer, in 15 months. We were able to obtain tumor, blood, saliva samples to perform genomic analyses, which were then merged with detailed clinical information. PRD, clinical, and genomic data generated from the first 12 patients and 14 samples have been released on cbioportal.org. Additional data will be released in six-month intervals. Initial results show high TMB and a UV signature in 3 out of 3 patients with HFNS AS. In addition, we identified 2 patients with HFNS AS who had extraordinary responses to immunotherapy. These findings suggest a common genomic basis for HFNS AS and could provide rationale for clinical interventions using checkpoint inhibitors for these AS. Analyses of additional samples are under way to further characterize mutational signatures in HFNS AS and implications for patient care. This study serves as proof of principle that patient-partnered genomics efforts can democratize cancer research for exceedingly rare cancers. Citation Format: Corrie Painter, Esha Jain, Michael Dunphy, Elana Anastasio, Mary McGillicuddy, Rachel Stoddard, Beena Thomas, Sara Balch, Kristin Anderka, Katie Larkin, Niall Lennon, Yen-Lin Chen, Andrew Zimmer, Esme O. Baker, Simone Maiwald, Jen Lapan, Jason L. Hornick, Chandrajit Raut, George Demetri, Eric S. Lander, Todd Golub. High mutation burden and response to immune checkpoint inhibitors in angiosarcomas of the scalp and face [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B085.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,854
Score d'incertitude au seuil0,331

Scores Codex et Gemma par catégorie

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

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 Opus0,023
Tête enseignante GPT0,332
Écart entre enseignants0,310 · 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 tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
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

Citations2
Publié2019
Routes d'admission1
Résumé présentoui

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