Dataset Information

Leveraging the CSF proteome toward minimally-invasive diagnostics surveillance of brain malignancies.

ABSTRACT:

Background

Diagnosis and prognostication of intra-axial brain tumors hinges on invasive brain sampling, which carries risk of morbidity. Minimally-invasive sampling of proximal fluids, also known as liquid biopsy, can mitigate this risk. Our objective was to identify diagnostic and prognostic cerebrospinal fluid (CSF) proteomic signatures in glioblastoma (GBM), brain metastases (BM), and primary central nervous system lymphoma (CNSL).

Methods

CSF samples were retrospectively retrieved from the Penn State Neuroscience Biorepository and profiled using shotgun proteomics. Proteomic signatures were identified using machine learning classifiers and survival analyses.

Results

Using 30 µL CSF volumes, we recovered 755 unique proteins across 73 samples. Proteomic-based classifiers identified malignancy with area under the receiver operating characteristic (AUROC) of 0.94 and distinguished between tumor entities with AUROC ≥0.95. More clinically relevant triplex classifiers, comprised of just three proteins, distinguished between tumor entities with AUROC of 0.75-0.89. Novel biomarkers were identified, including GAP43, TFF3 and CACNA2D2, and characterized using single cell RNA sequencing. Survival analyses validated previously implicated prognostic signatures, including blood-brain barrier disruption.

Conclusions

Reliable classification of intra-axial malignancies using low CSF volumes is feasible, allowing for longitudinal tumor surveillance.

SUBMITTER: Mikolajewicz N

PROVIDER: S-EPMC9639356 | biostudies-literature | 2022 Jan-Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Leveraging the CSF proteome toward minimally-invasive diagnostics surveillance of brain malignancies.

Mikolajewicz Nicholas N Khan Shahbaz S Trifoi Mara M Skakdoub Anna A Ignatchenko Vladmir V Mansouri Sheila S Zuccatto Jeffrey J Zacharia Brad E BE Glantz Michael M Zadeh Gelareh G Moffat Jason J Kislinger Thomas T Mansouri Alireza A

Neuro-oncology advances 20220101 1

<h4>Background</h4>Diagnosis and prognostication of intra-axial brain tumors hinges on invasive brain sampling, which carries risk of morbidity. Minimally-invasive sampling of proximal fluids, also known as liquid biopsy, can mitigate this risk. Our objective was to identify diagnostic and prognostic cerebrospinal fluid (CSF) proteomic signatures in glioblastoma (GBM), brain metastases (BM), and primary central nervous system lymphoma (CNSL).<h4>Methods</h4>CSF samples were retrospectively retri ...[more]

PMID: 36382110

Similar Datasets

Project description:In order to reduce medical facility overload due to the rise of the elderly population, modern lifestyle diseases, or pandemics, the medical industry is currently developing point-of-care and home medical device systems. Diabetes is an incurable and lifetime disease, accountable for a significant mortality and socio-economic public health burden. Thus, tight glucose control in diabetic patients, which can prevent the onset of its late complications, is of enormous importance. Despite recent advances, the current best achievable management of glucose control is still inadequate, due to several key limitations in the system components, mainly related to the reliability of sensing components, both temporally and chemically, and the integration of sensing and delivery components in a single wearable platform, which is yet to be achieved. Thus, advanced closed-loop artificial pancreas systems able to modulate insulin delivery according to the measured sensor glucose levels, independently of patient supervision, represent a key requirement of development efforts. Here, we demonstrate a minimally invasive, transdermal, multiplex, and versatile continuous metabolites monitoring system in the subcutaneous interstitial fluid space based on a chemically modified SiNW-FET nanosensor array on microneedle elements. Using this technology, ISF-borne metabolites require no extraction and are measured directly and continuously by the nanosensors. Due to their chemical sensing mechanism, the nanosensor response is only influenced by the specific metabolite of interest, and no response is observed in the presence of potential exogenous and endogenous interferents known to seriously affect the response of current electrochemical glucose detection approaches. The 2D architecture of this platform, using a single SOI substrate as a top-down multipurpose material, resulted in a standard fabricated chip with 3D functionality. After proving the ability of the system to act as a selective multimetabolites sensor, we have implemented our platform to reach our main goal for in vivo continuous glucose monitoring of healthy human subjects. Furthermore, minor adjustments to the fabrication technique allow the on-chip integration of microinjection needle elements, which can ideally be used as a drug delivery system. Preliminary experiments on a mice animal model successfully demonstrated the single-chip capability to both monitor glucose levels as well as deliver insulin. By that, we hope to provide in the future a cost-effective and reliable wearable personalized clinical tool for patients and a strong tool for research, which will be able to perform direct monitoring of clinical biomarkers in the ISF as well as synchronized transdermal drug delivery by this single-chip multifunctional platform.

Dataset Information

Leveraging the CSF proteome toward minimally-invasive diagnostics surveillance of brain malignancies.

Background

Methods

Results

Conclusions

Publications

Leveraging the CSF proteome toward minimally-invasive diagnostics surveillance of brain malignancies.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets