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Spatial Phenotyping Reveals Insights in Neuroscience: Highlights from SfN 2021

Spatial Phenotyping Reveals Insights in Neuroscience: Highlights from SfN 2021

We were thrilled to virtually attend the 2021 Society for Neuroscience (SfN) annual meeting. We collaborated with the Stanford School of Medicine’s department of Pathology and the Oregon Health & Science University to share data highlighting the power of spatial phenotyping to investigate neurological diseases and brain cancer.
Neurological diseases ranging from neurodegenerative diseases to cancer often have poor prognoses and are associated with a high cost of care. According to the Centers for Disease Control and Prevention (CDC) Alzheimer’s disease (AD) is the most common form of dementia, the 6th leading cause of death among adults in the United States, and among the top 10 overall leading causes of death. Parkinson’s disease, an impairment of nerve cells in the basal ganglia, is the 2nd most common neurodegenerative disease after Alzheimer’s disease. Glioblastoma multiforme (GBM) is the most common adult primary malignant brain tumor.
It is highly aggressive with about 90% mortality within 24 months following diagnosis. One thing that Alzheimer’s, Parkinson’s, and GBM have in common is that each has an undefined etiology; there is likely no single root cause, but rather an accumulation of several interactions affecting each person differently. Understanding these subtle and unique interactions is a necessary step in blazing the trail to novel therapeutic targets.
The transcriptional and proteomic profiles of neurological diseases and associated morphology are likely dependent on a combination of health status, other pathological conditions, sex, anatomical area of the brain, and disease stage. While single-cell RNA sequencing (scRNA-seq) has been instrumental in revealing cellular populations within the brain, it is lacking in spatial information and phenotypic characterization.
The scarcity of fresh human brain tissue imposes a bottleneck for RNA-seq studies, while paraffin-embedded tissues are widely available in most brain banks. Using PhenoCyclerᵀᴹ (formerly CODEX®) ultrahigh-plex imaging technology and the PhenoImagerᵀᴹ HT (formerly Vectra® Polaris™) whole-slide imaging technology, Akoya’s applications team partnered with the best and brightest across several institutions with expertise on biomarker panel development and neurological disease to maximize precious brain tissues to characterize cellular sub-populations, localization and the pathological features associated with neurodegenerative disease and cancer.

Spatial Phenotypic Characterization of Microglia and Pathogenic Features in Alzheimer’s Disease Brains

Akoya’s applications team collaborated with Alina Bogachuk from the lab of Dr. Bahareh Ajami at Oregon Health & Science University and used the PhenoCycler system to conduct spatial phenotypic characterization of microglia via ultrahigh-plex imaging of human brain tissue from patients with Alzheimer’s.
The team was able to generate the stunning images above using FFPE brain tissues and compare microglia in situ in the prefrontal cortex of patients with Alzheimer’s disease vs. control patients. The team was also able to investigate the pathogenic features of Alzheimer’s disease such as amyloid plaques.
The team conducted deep spatial phenotyping analysis using unsupervised clustering and nearest neighborhood analysis.
phenocycler alzheimers umap
phenocycler alzheimers nna
The unsupervised clustering of microglial phenotypes revealed multiple subtypes that distinctly localized around amyloid plaques. PhenoCycler spatial phenotyping enabled us to characterize microglia that surround amyloid plaques and neurofibrillary tangle (NFT)-filled neurons in different brain regions of AD, dementia affected individuals with no signs of amyloid plaque deposits, and tau mutant driven FTD affected individuals, and compare them with healthy age- and sex-matched individuals.
This study allowed us to characterize the changes of microglia phenotype in the immediate neighborhood of pathogenic features. Such observation will be instrumental to understanding the role of several late onset Alzheimer’s diseases associated genes and potentially identify novel drug targets.

Parkinson’s Disease-Associated LRRK2 Mutation and Cognition, through Rab12 Phosphorylation

To better understand the mechanisms behind the pathogenesis of Parkinson’s disease, Akoya’s applications team partnered with the Stanford University School of Medicine, Department of Pathology to investigate the relationship between leucine-rich repeat kinase 2 (LRRK2) and Rab12 phosphorylation.
LRRK2 is a large bifunctional enzyme with both GTPase and kinase activities. Mutations in the LRRK2 gene are the most common familial genetic predisposition for Parkinson’s disease. The clinical presentation of patients with LRRK2-PD is like that of patients with idiopathic PD. The pathogenic mutations of LRRK2 increase their kinase activity (gain-of-function) against exogenous and endogenous substrates. Studies have identified a subset of Rab GTPases as substrates of LRRK2, that are hyperphosphorylated by LRRK2 PD mutants. Current hypotheses are that LRRK2-PD mutant linked hyperphosphorylation of substrates is an underlying factor associated with LRRK2 PD.
Due to clinical overlap between LRRK2 PD and idiopathic PD, it is suspected that similar molecular pathogenicity may underly idiopathic PD. With this information the team set out to answer two questions: 1) Where in human brain and what type of cells exhibit LRRK2 signaling? and 2) Is LRRK2 kinase-related signaling enhanced in LRRK2 PD and/or idiopathic PD.
To answer these questions, the team validated a recombinant rabbit monoclonal antibody against Rab12 pSer106 (MJF-25-9) in immunocytochemistry for responsiveness to genetic and pharmacological modulators of LRRK2 kinase activity and found a strong correlation of pRab12 with LRRK2 kinase function. They then examined multiple regions throughout the human brain and found that although total Rab12 was detectable in multiple brain regions, pRab12 was only detected in the nucleus basalis of Meynert (NBM).
sfn phenocycler parkinsons
Staining of pRab12 and ChAT in (A) subsequent sections or the same section of the Nucleus Basalis of Meynert (NBM). (B) Muliplex fluorescence imaging used to evaluate localization of pRab12 and ChAT in the same neuron, along with NeuN, a general neuron marker.
Highly multiplexed fluorescent imaging with the PhenoCycler imaging technology were used to further correlate the localization of pRab12 in ChAT-positive cholinergic neurons of the NBM. Other regions, including substantia nigra which is a critical region in PD pathology, lack prominent pRab12 immunoreactivity. These findings represent a possible association between pRab12 and LRRK2 mutation and reduced cognitive decline in PD.

Characterizing the Immune Microenvironment of Glioblastoma

To investigate the various immune cells within the tumor microenvironment, biomarker specialist Dr. Agnes Haggerty and Akoya’s applications team used Akoya’s PD-1/PD-L1 panel kit to characterize the complex immune landscape of GBM tumors. Three distinct panels were used to stain the human FFPE tissues using the Leica Bond RX™ automated stainer. Multispectral whole-slide imaging was performed using the PhenoImager HT with optimized acquisition parameters, and scans were unmixed and analyzed with InForm® software. Spatial analysis and visualization were performed using phenoptr and phenoptrReports.
7-color panel optimized with the PhenoImager HT Automated Quantitative Multispectral Imaging (MSI) system
sfn pi glioblastoma
Akoya’s Opal dye technology together with the PhenoImager HT automated quantitative MSI system characterized the robust immune landscape of GBM. The team demonstrated that a PD-1/PD-L1 melanoma panel can be modified to interrogate phenotypes relevant to GBM. This flexibility could prove useful in developing new multispectral immunofluorescent panels to further characterize the complex immune signatures and interactions present in GBM and open the door for the design and implementation of therapeutics for GBM.

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