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Abstract 4113: A multimodal (PET/NIRF) smart probe for selectively identifying, grading, and visualizing astrocytic gliomas

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Abstract Astrocytic gliomas are the most common glioma subtype and constitute the majority of all primary brain tumor types. The malignancy of an astrocytic glioma is classified into one of four grades (I-IV) based on its infiltrative and proliferative characteristics, wherein the extent of this diffuse tissue and depth of embedment into normal brain tissue correlates to the degree of difficulty in accurately identifying and directly visualizing the requisite tumor tissue for achieving its complete resection. To date, no single- or multimodal imaging agent can noninvasively identify intracranial gliomas or accurately distinguish its grade as well as facilitate the direct visualization of its diffuse and deeply-embedded tissue in real-time. The standard imaging modalities for lesion detection (MRI and CT) provide anatomical information which have limited application in the pre- and post-surgical setting for identifying and grading tumor types as well as in monitoring for early-stage and recurrent growth, thereby creating a critical gap in evaluating invasive brain tumors that these techniques cannot successfully fill. Positron emission tomography (PET) is the ideal imaging modality that could fill this gap due to its ability to report on biological processes with superior sensitivity. However, conventional PET probes for gliomas operate on ubiquitously-expressed targets which provide insufficient or unreliable contrast levels between tumor and normal brain tissue or amongst low-grade gliomas. The standard of care for treating brain tumors entails unguided surgical resection followed by a tailored radio- and/or chemotherapy regimen that depends on tumor type and grade. As such, the extent of surgical resection largely governs patient survival time. Fluorescence-guided surgery (FGS) improves maximal resection of tumor tissue while preserving eloquent brain tissue. Primarily 5-aminolevulinic acid (5-ALA) is used in the FGS of brain tumors. However, its fluorescent product emits at short wavelengths and operates via nonselective signal accumulation, which affords limited tissue penetration and false-positive demarcations. The advent of near-infrared fluorescence (NIRF)-guided surgery leverages conventional (nontargeted and/or unactivatable) NIR fluorophores for tumor tissue visualization at 10-fold greater penetration depths, but poorly delineate tumor margins due to generating minimal signal accumulation and high background. To these ends, we have worked to develop a PET/NIRF smart probe for noninvasively identifying and grading intracranial astrocytic gliomas as well as affording direct visualization of its diffuse and deeply-embedded tumor tissue upon its application to NIRF-guided surgery. The multimodal smart probe uses a molecular logic gate design strategy to target a select active enzyme that serves as a validated prognostic factor for astrocytic gliomas. Citation Format: Kenneth S. Hettie, Eben L. Rosenthal, Frederick T. Chin. A multimodal (PET/NIRF) smart probe for selectively identifying, grading, and visualizing astrocytic gliomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4113.
Title: Abstract 4113: A multimodal (PET/NIRF) smart probe for selectively identifying, grading, and visualizing astrocytic gliomas
Description:
Abstract Astrocytic gliomas are the most common glioma subtype and constitute the majority of all primary brain tumor types.
The malignancy of an astrocytic glioma is classified into one of four grades (I-IV) based on its infiltrative and proliferative characteristics, wherein the extent of this diffuse tissue and depth of embedment into normal brain tissue correlates to the degree of difficulty in accurately identifying and directly visualizing the requisite tumor tissue for achieving its complete resection.
To date, no single- or multimodal imaging agent can noninvasively identify intracranial gliomas or accurately distinguish its grade as well as facilitate the direct visualization of its diffuse and deeply-embedded tissue in real-time.
The standard imaging modalities for lesion detection (MRI and CT) provide anatomical information which have limited application in the pre- and post-surgical setting for identifying and grading tumor types as well as in monitoring for early-stage and recurrent growth, thereby creating a critical gap in evaluating invasive brain tumors that these techniques cannot successfully fill.
Positron emission tomography (PET) is the ideal imaging modality that could fill this gap due to its ability to report on biological processes with superior sensitivity.
However, conventional PET probes for gliomas operate on ubiquitously-expressed targets which provide insufficient or unreliable contrast levels between tumor and normal brain tissue or amongst low-grade gliomas.
The standard of care for treating brain tumors entails unguided surgical resection followed by a tailored radio- and/or chemotherapy regimen that depends on tumor type and grade.
As such, the extent of surgical resection largely governs patient survival time.
Fluorescence-guided surgery (FGS) improves maximal resection of tumor tissue while preserving eloquent brain tissue.
Primarily 5-aminolevulinic acid (5-ALA) is used in the FGS of brain tumors.
However, its fluorescent product emits at short wavelengths and operates via nonselective signal accumulation, which affords limited tissue penetration and false-positive demarcations.
The advent of near-infrared fluorescence (NIRF)-guided surgery leverages conventional (nontargeted and/or unactivatable) NIR fluorophores for tumor tissue visualization at 10-fold greater penetration depths, but poorly delineate tumor margins due to generating minimal signal accumulation and high background.
To these ends, we have worked to develop a PET/NIRF smart probe for noninvasively identifying and grading intracranial astrocytic gliomas as well as affording direct visualization of its diffuse and deeply-embedded tumor tissue upon its application to NIRF-guided surgery.
The multimodal smart probe uses a molecular logic gate design strategy to target a select active enzyme that serves as a validated prognostic factor for astrocytic gliomas.
Citation Format: Kenneth S.
Hettie, Eben L.
Rosenthal, Frederick T.
Chin.
A multimodal (PET/NIRF) smart probe for selectively identifying, grading, and visualizing astrocytic gliomas [abstract].
In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL.
Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4113.

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