Precision Medicine by Targeting Cell Adhesion in Melanoma
通过靶向黑色素瘤细胞粘附的精准医学
基本信息
- 批准号:10179329
- 负责人:
- 金额:$ 17.09万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-08-01 至 2022-07-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAdhesionsAdjuvant TherapyAffectAgeAnimal HousingAnxietyAreaBiologicalBiologyBiomedical ResearchBiopsyBiopsy SpecimenBreslow ThicknessCell AdhesionCell CommunicationCharacteristicsClinicClinicalClinical DataComplexComputer softwareCore FacilityCutaneous MelanomaCytotoxic T-LymphocytesDNAData SetDecision MakingDermatologistDevelopmentDiagnosisDiagnosticDiagnostic ProcedureDrug CombinationsEuropeExtracellular MatrixFibronectin ReceptorsFibronectinsGene ExpressionGoalsGrowthHandHealthcareHistologicHistologyHospitalsImmune checkpoint inhibitorImmunotherapyIn Situ HybridizationIndolentInfiltrationInfrastructureInnovative TherapyIntegrinsInternationalK-Series Research Career ProgramsKnowledgeLaboratoriesLeadLeadershipLesionLifeLinkMainstreamingMalignant - descriptorMalignant NeoplasmsMalignant neoplasm of prostateMedical StaffMedicineMelanoma CellMentorsMethodologyMethodsMicrofluidicsMicroscopeMitoticModelingMolecularMolecular ProfilingMyofibroblastNamesNeoplasm MetastasisOncogenesOrganPatientsPhysiciansPigmentsPositive Lymph NodeProceduresPublishingRNARelapseResearchResearch MethodologyResearch PersonnelResistanceResourcesRiskScientistScreening for Skin CancerSentinel Lymph NodeSentinel Lymph Node BiopsyServicesSideSkin CancerSpecialistStandardizationStatistical MethodsStatistical ModelsStructureT-LymphocyteTechniquesTechnologyTestingTherapeuticThickThinnessTissuesTrainingTraining ActivityTranslatingTumor Cell InvasionUnited StatesUp-RegulationWalkingWorkanimal careanti-PD1 therapyanticancer researchbasebiological systemscancer cellcostdesigndiagnostic biomarkerdraining lymph nodeexperienceexperimental studyfallshigh riskin vivoin vivo Modelindexinginnovationinsightlymph nodesmedical specialistmelanocytemelanomamouse modelnovelnovel therapeutic interventionnovel therapeuticsoptical imagingovertreatmentprecision medicinepreventresponserisk stratificationside effectskillsstandard of carestatistical learningtissue archive
项目摘要
PROJECT SUMMARY/ABSTRACT
In the proposed research, we address a problem that is common not just to melanoma, but also to
other forms of cancer, such as prostate cancer, and that has been widely discussed recently. While
we as dermatologists encourage patients to undergo skin cancer screening exams to detect
melanoma early, it remains challenging to differentiate the truly aggressive from the indolent or
nonclinical pigmented lesions. This is true even after a melanoma has been biopsied and examined
under the microscope. As a result, there is massive over-diagnosis and overtreatment, specifically
with respect to sentinel lymph node (SLN) biopsies, that is costly, has side effects, requires precious
hospital infrastructure and induces substantial patient anxiety.
Surprisingly, and despite decades of research on cancer, assessment of metastasis risk in primary
cutaneous melanoma continues to be based primarily on tumor invasion depth (also referred to
Breslow depth), a method that was introduced 45 years go. While Breslow depth tends to work well at
the extreme ends of the spectrum, most melanomas fall into a grey zone where Breslow depth with or
without additional tissue-derived and clinical variables (such as patient age) does not predict the true
biology of melanoma well. Breslow depth continues to be popular because alternative methods,
including molecular-based methods, are either ineffective, have not been appropriately validated or
lack a strong biological rationale. This in turn inhibits the development of new and innovative
therapies.
Here we will study a method that quantifies changes in integrin-linked cell adhesion to better
differentiate high-risk (defined as SLN positive melanoma) from biologically indolent melanoma. First,
we will study consecutive cases of cutaneous melanoma from across the United States and Europe
and correlate a molecular profile of cell adhesion with SLN status. Second, we will study how the
inhibition of certain aspects of integrin adhesion affects melanoma growth and metastasis in vivo. We
expect that our research will validate methods to identify high-risk melanoma that outperform the
standard of care, reduce the rate of unnecessary SLN procedures and identify patients with high-risk
melanoma overlooked by current procedures. Moreover, a better understanding of the molecular
machinery that drives metastasis will create new therapeutic opportunities.
The candidate’s long term goal is discover novel characteristics of malignant melanocytes that enable
the development of new and innovative diagnostic methods and therapies. The mentored career
development award will help the candidate acquire new methodological, professional and leadership
skills to independently, successfully and meaningfully contribute to the fields of cell
adhesion/cancer/melanoma research in the years to come. Specifically, the plan is to pursue the
following training activities:
1.) Acquire expertise in studying melanoma using mouse models; use these models to test and
optimize drugs and drugs combinations.
2.) Acquire experience in interpreting the histological features of melanoma; broaden my
understanding of the biological concepts used by dermatopathologists to characterize melanoma.
3.) Acquire expertise in designing diagnostic biomarker studies; learn statistical methods,
specifically methods that can be used to analyze complex datasets.
4.) Build the professional and leadership skills to bring together and lead an international
consortium of melanoma investigators.
The candidate will be mentored by a team of national experts in the field of cancer research.
Mentoring and research will be carried out at the Mayo Clinic in Rochester, MN. Mayo Clinic offers
core facility services for all mainstream standardized biomedical research methods. This includes
tissue archives and bio-banking, animal housing and animal care, optical imaging, including high-end
confocal microscopes, all methods related to histology, including RNA and DNA in-situ hybridization,
targeted gene expression-based methods including microfluidic Fluidigm technology, and all
mainstream ‘omics’ methods. All services are fully staffed with trained technicians. Moreover, there is
scientific staff available to trouble-shoot experiments. These resources are all within walking distance
from the candidate’s laboratory. Moreover, Mayo Clinic has a large staff of medical indexers, software
programmers, application specialist and bio-information scientists. Because of the size of the clinic,
there are medical specialists and subspecialists on hand for all areas of medicine.
项目成果
期刊论文数量(21)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Deep learning for dermatologists: Part II. Current applications.
- DOI:10.1016/j.jaad.2020.05.053
- 发表时间:2022-12
- 期刊:
- 影响因子:13.8
- 作者:Puri P;Comfere N;Drage LA;Shamim H;Bezalel SA;Pittelkow MR;Davis MDP;Wang M;Mangold AR;Tollefson MM;Lehman JS;Meves A;Yiannias JA;Otley CC;Carter RE;Sokumbi O;Hall MR;Bridges AG;Murphree DH
- 通讯作者:Murphree DH
Prognostic significance of sentinel lymph node status in thin melanoma: a retrospective analysis.
薄黑色素瘤前哨淋巴结状态的预后意义:回顾性分析。
- DOI:10.1111/ijd.17000
- 发表时间:2024
- 期刊:
- 影响因子:3.6
- 作者:Meves,ElenaS;Meves,Alexander
- 通讯作者:Meves,Alexander
Deep learning for dermatologists: Part I. Fundamental concepts.
- DOI:10.1016/j.jaad.2020.05.056
- 发表时间:2022-12
- 期刊:
- 影响因子:13.8
- 作者:Murphree DH;Puri P;Shamim H;Bezalel SA;Drage LA;Wang M;Pittelkow MR;Carter RE;Davis MDP;Bridges AG;Mangold AR;Yiannias JA;Tollefson MM;Lehman JS;Meves A;Otley CC;Sokumbi O;Hall MR;Comfere N
- 通讯作者:Comfere N
β3 integrin immunohistochemistry as a method to predict sentinel lymph node status in patients with primary cutaneous melanoma.
- DOI:10.1111/ijd.15125
- 发表时间:2020-10
- 期刊:
- 影响因子:3.6
- 作者:Quattrocchi E;Sominidi-Damodaran S;Murphree DH;Meves A
- 通讯作者:Meves A
Validation of CP-GEP (Merlin Assay) for predicting sentinel lymph node metastasis in primary cutaneous melanoma patients: A U.S. cohort study.
- DOI:10.1111/ijd.15594
- 发表时间:2021-07
- 期刊:
- 影响因子:3.6
- 作者:Yousaf A;Tjien-Fooh FJ;Rentroia-Pacheco B;Quattrocchi E;Kobic A;Tempel D;Kolodney M;Meves A
- 通讯作者:Meves A
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