Count Me In: Partnering with patients to define the clinical and genomic landscape of rare aggressive sarcomas in children and adults
Count Me In: Partnering with patients to define the clinical and genomic landscape of rare aggressive sarcomas in children and adults
批准号:
10237259
负责人:
Katherine A Janeway
金额:
$321.09万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-09-01 至 2025-08-31
关键词:
AddressAdultAgeBehavioral ResearchBehavioral SciencesBiologyBloodBone neoplasmsCancer PatientCaringChildChildhoodClinicalClinical DataClinical ResearchClinical TrialsCommunitiesComputational BiologyComputer AnalysisConsentCountryDana-Farber Cancer InstituteDataData ReportingData ScienceDatabasesDevelopmentDiagnostic ProcedureFailureGenomeGenomicsGeographyGoalsIncidenceInstitutesInstitutionIntervention StudiesLeadershipMalignant NeoplasmsMedical RecordsMesenchymalModelingMolecularMorbidity - disease rateObservational StudyParticipantPatient RecruitmentsPatientsPrevention strategyPrimary NeoplasmPrognostic MarkerResearchRisk FactorsRural MinoritySalivaSamplingSmooth MuscleSpecimenSurvival RateTimeTissue SampleTranslational ResearchTumor TissueWorkanticancer researchbonecancer typecell free DNAclinical databasedata archivedata de-identificationempoweredexomeexperiencegenomic dataimprovedleiomyosarcomaliteracymembernovelosteosarcomapatient engagementpatient populationprimary bone cancerrare cancersarcomashared databasesocial mediatargeted treatmenttherapeutic biomarkertherapy resistanttranscriptometreatment responsetreatment strategytumortumor DNAweb sitewhole genome
中文摘要
骨肉瘤(OS)和平滑肌肉瘤(LMS)是非常罕见的癌症,都是肉瘤的亚型。
英文摘要
Osteosarcoma (OS) and leiomyosarcoma (LMS) are exceedingly rare cancers, both subtypes of sarcoma,
that arise in bone and smooth muscle respectively. There has been a failure to improve survival rates or decrease
treatment-related morbidity in OS/LMS due to insufficient characterization of the genomic landscape, resulting
in a lack of targeted therapeutic approaches, diagnostic methods, and preventive strategies. There is an urgent
need for a large, shared database of clinical and genomic data in OS and LMS. Yet, because of the rarity of
these tumor types as well as other challenges in patient recruitment and the genomic characterization of these
tumors, to date it has been difficult to generate this data. The overarching goal of this proposal is to engage
adult and pediatric participants with OS and LMS as partners to generate a shared database of clinical,
genomic, molecular, and patient-reported data. This should accelerate discoveries that drive novel treatment
strategies, new clinical trials, and new standards of care. The Count Me In PE-CGS U2C Research Center will
leverage our experience in patient engagement, genome characterization, computational analysis, and
behavioral research to create and launch two patient-partnered projects to generate this clinicogenomic
data. We will build two websites with patients in the OS and LMS communities—the Osteosarcoma Project
(OSproject) and the Leiomyosarcoma Project (LMSproject)—and consent 3,000 patients over the course of the
study. We will collect medical records, patient-reported data, archival tumor tissue samples, and saliva and blood
for genomic analysis. We will generate clinically annotated genomic data from at least 750 tumor specimens,
500 circulating tumor DNA specimens, and corresponding germline specimens and share the de-identified data
widely. At the same time, we will study and optimize the approach to patient engagement in cancer research,
particularly among rural and minority participants and participants across a range of literacy levels, ages, and
stages in development. To accomplish these goals, we will build on a well-established interdisciplinary team from
the Broad Institute and Dana-Farber Cancer Institute with members who have pioneered these approaches. Our
leadership (Wagle, Janeway) and Units are comprised of experts in patient-partnered cancer research (Wagle,
Painter), sarcoma clinical and translational research (Janeway, George, Crompton, Raut), genome
characterization, analysis, and clinical interpretation (Gabriel, Getz, Van Allen, Wagle, Janeway),
computational biology/data science (Getz, Van Allen, Philippakis), and behavioral science (Mack, Rebbeck).
Our Center will uncover the key clinicogenomic features of OS/LMS, integrate them into a single comprehensive
database with a goal of accelerating research and improving the lives of these patients. In doing so, we also
aim to present a general approach to patient-partnered research that can be disseminated broadly and applied
to other tumors types and patient communities.
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