Optogenetic engineering of tumor topography in native tissue environments
Optogenetic engineering of tumor topography in native tissue environments
批准号:
10687660
负责人:
Ravikanth Maddipati
金额:
$143.74万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-09-22 至 2026-08-31
关键词:
AchievementAnatomyBar CodesBehaviorBiologyCellsDevelopmentDiseaseDisease ProgressionEngineeringEnterobacteria phage P1 Cre recombinaseEnvironmentFutureGene ActivationGenetic ModelsGenetic RecombinationGenetically Engineered MouseGoalsHeadHead of pancreasHistologicHumanInter-tumoral heterogeneityLesionLightLinkLocationMalignant NeoplasmsMalignant neoplasm of pancreasMethodsModelingMolecularMutationOncogenesOncogenicOrganPatternPhenotypePositioning AttributePrognosisProtein EngineeringProteinsRegulationResearchSpecificitySystemTailTail of pancreasTechnologyTissuesTumor BiologyTumor Suppressor Proteinsanticancer researchclinical phenotypeclinically significanthuman diseasein vivoinducible Creinsightmolecular phenotypemouse modelnovelnovel strategiesoptogeneticspancreatic neoplasmrecombinaseregional differencescreeningsingle cell sequencingspatiotemporalstemtargeted treatmenttumortumor heterogeneity
中文摘要
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英文摘要
Project Summary: In nearly every cancer, tumors demonstrate a predilection for certain locations within a tissue
and this is associated with unique clinical phenotypes. For example, in pancreatic cancer, lesions that arise in
the head of the pancreas have a better prognosis and favorable histological subtypes compared to those
developing in the tail. Thus, the anatomic position of a tumor within an organ can provide the context on which
mutations act to define clinical and molecular phenotypes. Despite the clinical significance, the mechanisms that
determine regional differences in tumor phenotypes remains enigmatic. The overall goal of this proposal is to
develop novel approaches to gain mechanistic insights into how anatomic position directs tumor phenotypes.
A major technical gap in our ability to interrogate tumor topography in disease progression is the lack of
relevant genetic models that recapitulate spatial patterns and behaviors of human cancers. For example,
pancreatic tumors can be readily generated in multiple murine models. However, localizing tumor formation to
the head or tail of the pancreas is not possible. This stems from current tumor models that use Cre-recombinase
technology to induce oncogenic transformation by activating oncogenes or deleting tumor suppressors in tissues.
While tissue specificity can be achieved in some cases, targeting Cre activity and by extension oncogenic
mutations to specific anatomic locations in a tissue is not possible and limits spatial control of tumor formation.
To overcome these limitations, we propose to add a layer of spatial/regional control to tumor induction in
genetically engineered murine models (GEMMs). We accomplish this by developing and leveraging optogenetic
technologies for cancer research. Optogenetics involves introducing genetically encoded light sensitive proteins
to a cell that can be activated by light and enables spatially defined protein regulation in tissues. Here we propose
to engineer an optogenetic recombinase platform that allows for control of Cre activity with targeted light beams
to enable precise spatial and temporal control of tumor formation. Though risky, we employ a systematic strategy
to accomplish this. First, we will combine protein engineering with in vivo barcoded screening methods to develop
a novel photoactivable Cre capable of eliminating background recombinase activity while maintaining robust
recombination with light. Second, we will develop this construct into an optogenetic-Cre GEMM and optimize
parameters to enable precise gene activation at a regional and single-cell level. Finally, we will integrate this
system into Cre inducible oncogene models to generate tumors within defined anatomic locations and
characterize their phenotypes and molecular features with single-cell sequencing technologies.
The potential to control spatiotemporal patterns of tumor development in vivo would be a major
achievement in cancer research. This will transform our ability to model spatial patterns of human cancers and
study the impact on tumor biology. Furthermore, our technology could advance research beyond cancer, as the
biology of many diseases are influenced by anatomic location but cannot be interrogated with existing models.
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