Spatial Proteomics
Spatial Proteomics - Related Videos
09:29
Skeletal Muscle Gender Dimorphism from Proteomics
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Cited by 4 •
2011
A straight-forward set of methods to isolate and determine the identity of the most abundant proteins expressed in skeletal muscle. About 800 spots are discerned on a two-dimensional gel from 10 mg muscle; this allows for the determination of gender-specific protein expression. These methods will give equivalent results in most tissues.
09:20
Proteomic Sample Preparation from Formalin Fixed and Paraffin Embedded Tissue
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Cited by 50 •
2013
Archival formalin fixed and paraffin embedded (FFPE) clinical samples are valuable material for investigation of diseases. Here we demonstrate a sample preparation workflow allowing in-depth proteomic analysis of microdissected FFPE tissue.
14:23
Bottom-up and Shotgun Proteomics to Identify a Comprehensive Cochlear Proteome
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Cited by 6 •
2014
Proteome analysis of the cochlear sensory epithelium can be challenging due to its small size and because membrane proteins are difficult to isolate and identify. Both membrane and soluble proteins can be identified by combining multiple preparative methods and separation techniques along with high-resolution mass spectrometry.
08:52
Spatial Molecular Imaging of the Glycome Using Mass Spectrometry
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Cited by 1 •
2025
This protocol details the key steps to enable rigorous and reproducible measurement of both glycogen and N-linked glycans using mass spectrometry imaging.
07:51
Spatial Cueing
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2023
Source: Laboratory of Jonathan Flombaum—Johns Hopkins University Attention refers to the limited human ability to select some information for processing at the expense of other stimuli in the environment. Attention operates in all sensory modalities: vision, hearing, touch, even taste and smell. It is most often studied in the visual domain though. A common way to study visual attention is with a spatial cueing paradigm. This paradigm allows researchers to measure the consequences of focusing...
FAQs
Preserving spatial relationships shows whether a protein pattern is concentrated in malignant regions, adjacent immune cells, stromal areas, or broader tissue zones. Conventional protein measurements may report overall abundance while losing this localization. The spatial context therefore helps connect protein patterns with tumor organization and heterogeneity, improving interpretation of cancer biology.
Rather than treating a tumor as a uniform sample, investigators can compare protein patterns across malignant, immune, and stromal regions. Those regional differences expose heterogeneity within the tumor microenvironment and help separate signals associated with cancer cells from signals arising in neighboring cells. This distinction strengthens interpretation of tissue-level protein measurements.
Spatially resolved protein patterns can be examined alongside cancer features named in the overview, including signaling, invasion, treatment response, and disease progression. The key analytical question is not only how much protein is present, but where it occurs and which defined regions share or differ in that pattern. This links molecular measurements to tissue behavior.
Interactions are interpreted through the arrangement of proteins across defined cellular regions. When proteins occur in related locations, spatial analysis can help investigators examine their association within a tumor microenvironment rather than relying only on average abundance. This regional view supports investigation of signaling relationships and may clarify how local protein organization relates to invasion or progression.
A study can combine protein detection with imaging, tissue mapping, or spatially resolved molecular analysis. These approaches retain the location of measured proteins and associate observations with defined cellular or tissue regions. The resulting map can then be compared across tumor, immune, and stromal areas to interpret abundance, distribution, and interactions.
Spatial proteomics can support biomarker discovery by associating protein patterns with specific tissue or cellular regions. A candidate marker may be more informative when its abundance or distribution is interpreted in relation to malignant, immune, or stromal compartments. This regional information can help researchers investigate whether a signal is linked to tumor heterogeneity or disease behavior.
By revealing protein patterns across tumor microenvironments, the approach can provide evidence relevant to treatment response and disease progression. Those observations may help distinguish patients or tumor regions with different molecular characteristics, supporting patient stratification and the development of more precisely targeted therapies. The value comes from connecting candidate protein signals to their spatial cancer context.