Molecular pathology involves study of DNA/RNA or protein in vivo. It gives the answers to the questions like where cells are located in tissue, how they interact and make impact on the tissue microenvironment
Important applications of molecular pathology includes biomarker discovery, pathway analysis, spatial omics, etc. It plays vital role in clinical research involving cancer research, drug response validation and more.
Currently spatial transcriptomics and spatial protein profiling platforms are providing great insights about RNA and proteins inside the tissues
Molecular pathologist use various tissue imaging techniques to investigate diseased tissue or organs to identify and quantify disease markers. Based on their results, a diagnosis can be made and the optimal treatment can be identified. Clinical researchers track the interaction of tumor cells and immune cells by analyzing RNA and protein expression within tissue microenvironment.
In vivo tissue imaging is usually done by the microcopy techniques, FISH for nucleic acid and IHC for protein. This techniques are limited by the sample multiplexing as well as analyte multiplexing. And Important aspect of the spatial biology is the resolution, resolution to the single cell or subcellular level can only provide essential information from tissue and its microenvironment.
Using spatial multiomics researchers can connect the genotype to phenotype and fuel discovery of novel drug targets and biomarkers which can not be obtain by single omics methods.
Transcriptome profiling has been widely used to understand the genetic regulation of a particular cell type. It can offer valuable information on the significant biological processes behind the maintenance of the functionality of the cell.
Transcriptome Analysis may help confirm tumor diagnosis. In cases of diagnostically challenging tumors, such as tumors of unknown primary origin, Transcriptome Analysis can help predict the likely tissue or origin through gene expression, helping to improve diagnosis and classification.
Whole transcriptome analysis aims at capturing both coding and non-coding RNA and quantifying gene expression heterogeneity in cells, tissues, organs and even a whole body.
Our GeoMx Digital Spatial Profiler is the perfect platform for the spatial transcriptomics and proteomics analysis. It allows researchers to do tissue imaging as well as molecular profiling.
It is the one solution from discovery to translational research and more flexible and robust for spatial biology study.
WTA & CTA an answer for Transcriptome Profiling
Understanding tissue heterogeneity is critical to answering key biological questions in human health and disease. Single-cell RNA sequencing can detect cellular heterogeneity but lacks the spatial context needed to understand the relationship of cell types to disease pathology.
The newly available GeoMx Whole Transcriptome Atlas (WTA) accelerates scientific discovery by resolving tissue heterogeneity and the true molecular basis of disease.
The GeoMx® Cancer Transcriptome Atlas (CTA) is designed for comprehensive profiling of tumor biology, tumor microenvironment, and immune response. Profile RNA expression of over 1,800 genes simultaneously with spatial resolution from distinct regions of interest with a single tissue section using the GeoMx Digital Spatial Profiler.
CTA and WTA enable transcriptome-scale spatially resolved profiling to enable molecular characterization of single FFPE tissue sections, creating a workflow that helps resolve the need to preserve these tissues while also deeply characterizing their morphology, gene expression, and interplay of the two
After genomics and transcriptomics, proteomics is the next step in the study of biological systems. It is more complicated than genomics because an organism's genome is more or less constant, whereas proteomes differ from cell to cell and from time to time. Distinct genes are expressed in different cell types, which means that even the basic set of proteins produced in a cell must be identified.
In the past, this phenomenon was assessed by RNA analysis, which was found to lack correlation with protein content. It is now known that mRNA is not always translated into protein, and the amount of protein produced for a given amount of mRNA depends on the gene it is transcribed from and on the cell's physiological state. Proteomics approaches facilitate the analysis of proteins present in cells and tissues. It not only confirms the presence of the protein but also provides a direct measure of its quantity.
Spatial proteomics have enabled the explanation of protein’s spatial localization within cells, which has enhanced our understanding of their form and function. Different methods have emerged in the past years to visualize protein positioning, which might vary as a function of cell type, cell cycle progression or disease state. Spatial proteomics has thereby provided unprecedented insight into biological processes not only from a fundamental cell biology perspective, but also from a clinical perspective, to study how protein localization changes in pathogenic cells, which could prove useful for finding biomarkers and developing new therapies.
There are two main experimental approaches to spatial proteomics: high-throughput imaging to visualize all proteins within a cell or within a compartment of interest; and quantitative mass spectrometry, to identify subcellular protein networks by organellar profiling or interactomics.
Spatial proteomics study by using Rapiflex and timsTOF Flex has enabled researchers to identify and quantitate proteins on the basis of matrix assisted or trapped ion mobility.
Rapiflex has a unique smartbeam 3D laser that fires at a repetition rate of up to 10 kHz. The smartbeam 3D laser features a laser diameter of 5 µm, enabling MALDI Imaging of tissue at 20 µm spatial resolution. High Speed - up to 40 true pixels / second yields faster and better images. Integrating 2 software solution flexImaging and SCiLS™ Lab.
timsTOF FLEX has a dual source which is ideal to conduct robust ESI and MALDI measurements. It can spatially resolve a wide range of molecules directly from tissue using one platform. It can perform identification and quantification due to PASEF mode. It provides analytical data for spatial proteomics, lipidomics, glycomics, or metabolomics. It supports study of tumor microenvironment of cancer containing a combination of healthy cells, tumor cells, connective tissue, blood vessels, and inflammation in different ratios at different time points can be studied with deep SpatialOMx analysis.
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Differential Expression Between Samples
MARKET SEGMENT-WISE APPLICATIONS
Mainly in cancer research and studying diagnosis to translational research
Essential in vaccine development, studying the drug validation to therapeutic response