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Enregistrement W4205712587 · doi:10.1158/1538-7445.sabcs20-ot-18-01

Abstract OT-18-01: The metastatic breast cancer project: Generating the clinical and genomic landscape of metastatic breast cancer through patient-partnered research

2021· article· en· W4205712587 sur OpenAlexaboutno aff
Nikhil Wagle, Corrie Painter, Elana Anastasio, Michael Dunphy, Mary McGillicuddy, Esha Jain, Brett N. Tomson, Tania G. Hernandez, Beena Thomas, Dewey Kim, Alyssa L. Damon, Shahrayz Shah, Rafael Ramos, Colleen Nguyen, Oneil Lee, S Winnicki, Sara Balch, Rachel Stoddard, Taylor Cusher, Parker Chastain, Jorge Gómez Tejeda Zañudo, Jorge E. Buendia-Buendia, Ofir Cohen, Netsanet Tsegai, Lauren Sterlin, Ulcha F. Ulysse, Imani Boykin, Kate Sine, Oyin Alao, Jacqueline Lucia, Eric S. Lander, Todd R. Golub

Notice bibliographique

RevueCancer Research · 2021
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueCancer Genomics and Diagnostics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBreast cancerMetastatic breast cancerMedicineBiobankCancerInternal medicineOncologyMedical recordExome sequencingFamily medicineBioinformaticsBiologyGeneticsGene

Résumé

récupéré en direct d'OpenAlex

Abstract The Metastatic Breast Cancer Project (MBCproject) is an ongoing research study that directly engages patients (pts) through social media and advocacy groups, and empowers them to share their samples, clinical information, and experiences. The goal is to create a publicly available dataset of linked genomic, clinical, and pt-reported data to enable research. In collaboration with pts, advocates, and advocacy groups, a website (MBCproject.org) was developed that allows pts with metastatic breast cancer (MBC) anywhere in the US or Canada to register. From 10/20/15-3/31/20, 5708 women and men with MBC registered for the MBCproject. Registered pts are sent an online consent form that asks for permission to obtain and analyze their medical records and samples. Consented pts are sent a saliva and/or blood kit and asked to mail back a saliva sample, which is used to extract germline DNA, and/or a blood sample, which is used to extract germline DNA and cell free DNA (cfDNA). We contact participants’ medical providers to obtain medical records and a portion of their stored tumor biopsies. 3245 pts receiving care at over 1700 different institutions have consented to share medical records and tumor/saliva/blood samples and to have genomic analysis performed. Whole exome sequencing (WES) is performed on tumor DNA, germline DNA, and cfDNA; transcriptome sequencing (RNA-seq) is performed on tumor RNA. Medical records and pt-reported data are abstracted to create a detailed clinical record for each pt. Table 1 highlights clinical data collection, biospecimen acquisition, and genomic data generation to date. Examples of clinicogenomic analyses are shown in Table 2. De-identified linked genomic, clinical, and pt-reported data is shared regularly via public and semi-public databases (mbcproject.org, cBioPortal, dbGaP, NCI Genomic Data Commons). To date, this data has been cited in over 20 published journal articles. Study updates are shared with participants regularly. The MBCproject continues to enroll new patients, generate additional data, and perform integrated clinical and genomic analyses with the goal of building a dataset that is representative of patients with MBC. We have partnered with over 30 non-profit breast cancer advocacy groups. We also have several community engagement efforts underway to more directly reach patients in underrepresented communities, including partnerships with faith-based organizations and colleges/universities, as well as targeted engagement with the African American community. In addition, in partnership with Latinx patients, advocates, and researchers, the project has been translated into Spanish and is expected to launch in late 2020. Partnering directly with pts rapidly enables thousands of pts to remotely share tumors, blood, saliva, and medical records to accelerate research. The resulting publicly shared clinically annotated database is a resource that allows researchers to identify patients with specific phenotypes, who have often been challenging to identify with traditional approaches. Clinical data collection, biospecimen acquisition, and genomic data generation:NumberConsent signed (US & CA)3245 ptsSurvey #1 submitted(demographics, diagnosis details, receptor status, clinical experiences)3245 ptsSurvey #2 submitted(pathology details, sites of metastasis, treatments with start and stop dates)1638 ptsMedical record received1352 ptsSaliva sample received2004 ptsBlood sample received1121 ptsTumor samples received585 tumor samples from 424 ptsDigital image of tumor slide H&E generated585 tumor samplesWES from germline complete458 germline samplesWES from tumor (primary and metastatic) samples complete343 tumor samplesRNA-seq from tumor (primary and metastatic) samples complete228 tumor samplesULP-WGS from cfDNA (taken in metastatic setting) complete993 blood samplesWES from circulating tumor DNA (taken in metastatic setting) complete143 blood samples CohortConsented (US & CA)Tumor WES completeTumor RNA-seq completePts diagnosed < 40 yrs of age107312071De novo MBC112712183Late recurrence (>5 years after dx)8307752Long term survivors (MBC > 10yrs)158115Resistance to CDK4/6 inhibitors70914839NED at time of f/u survey4238939Triple Negative Breast Cancer3107531Patients with 2 or more tumor biopsies / cfDNA samples collected by the MBCproject2876138 Citation Format: Nikhil Wagle, Corrie Painter, Elana Anastasio, Michael Dunphy, Mary McGillicuddy, Esha Jain, Brett Tomson, Tania G. Hernandez, Beena Thomas, Dewey Kim, Alyssa L. Damon, Shahrayz Shah, Rafael Ramos, Colleen Nguyen, Lee O'Neil, Sarah Winnicki, Sara Balch, Rachel Stoddard, Taylor Cusher, Parker Chastain, Jorge Gomez Tejeda Zanudo, Jorge Buendia-Buendia, Ofir Cohen, Netsanet Tsegai, Lauren Sterlin, Ulcha F. Ulysse, Imani Boykin, Kate Sine, Oyin Alao, Jacqueline Lucia, Eric S. Lander, Todd R. Golub. The metastatic breast cancer project: Generating the clinical and genomic landscape of metastatic breast cancer through patient-partnered research [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr OT-18-01.

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)0,018
score de la tête « metaresearch » (Gemma)0,038
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: aucune
Score de désaccord entre enseignants0,025
Score d'incertitude au seuil0,097

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0180,038
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0030,001
Communication savante0,0040,002
Science ouverte0,0020,009
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0230,006

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 Opus0,166
Tête enseignante GPT0,466
Écart entre enseignants0,300 · 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
Publié2021
Routes d'admission1
Résumé présentoui

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