Biomarker Quantification and Colocalization

Biomarker Quantification and Colocalization2019-09-11T11:09:23-05:00

Overview

Immunohistochemistry (IHC) is a powerful tool for the examination of the distribution of relevant biomarkers in tissue samples. Immunohistochemistry is frequently conducted to determine the extent of and changes to populations of cells, to examine for the presence of receptors and markers which are indicated in diseases, and to evaluate the effect of drug treatments on animal and human tissues. Traditionally, analysis of slides prepared with IHC techniques involved subjective analysis by a pathologist, often including a score indicating the extent of the presence or absence of a given marker. With modern computational techniques and image processing, analysis of IHC sections can be accomplished quantitatively on large numbers of tissue sections in a fraction of the time.

Visikol offers a suite of services for the quantification and analysis of IHC sections, to examine the extent and distribution of biomarkers important in disease pathology. Evaluation of the colocalization of various biomarkers allows for quantification of the breakdown of subpopulations of cells, determination of the coincidence between biomarkers of interest, and examination of the changes to protein expression of specific cell types.

Protocol

InstrumentAperio XT2 Slide Scanner
Analysis MethodBrightfield Imaging
MarkersImmunohistochemistry (chromogenic or fluorescence)
Mason’s trichrome
Hematoxylin
Other stains available on request
Sample SubmissionWhole Tissue fixed and stored in PBS with 0.05% azide
Formalin Fixed Paraffin Embedded (FFPE) tissue blocks
Tissues embedded in OCT
Pre-stained and mounted slides
Digitized slide images
Imaging Parameters20X, 40X magnification
Image Analysis Cell counting
Colocalization analysis
Nearest neighbor analysis
Data DeliveryWhole Slide Images in RGB format, ROI masks (e.g. CD3+ cells),
Data tables containing cell counts or area for biomarkers
Histograms of spatial distribution for nearest neighbor analysis
Statistical analysis
Other quantification strategies available on request

General Procedure

  1. Tissue sample is transferred to Visikol in PBS w/ 0.05% azide or in a form most appropriate for the customer (e.g. FFPE, OCT compound).
  2. Alternatively, mounted and stained slides or digitized images of IHC sections can be sent for analysis.
  3. The sample is processed, sectioned, and stained using immunohistochemistry techniques.
  4. The sample slides are imaged with high-throughput slide scanner at desired magnification.
  5. The images are then processed and analyzed according to customer specifications.
  6. Images and quantification report are then transferred to the customer.

Representative Data

Evaluation of Hormone Receptors in Clinical Breast Cancer Biopsy Sections

Figure 1A. Tissue section from biopsy of female patient diagnosed with invasive ductal adenocarcinoma, stained for estrogen receptor (ER); Move slider to reveal segmentation of ER+ cells, which are highlighted in red.

Figure 1B. Total number of cells, number of ER+, PR+, and ER+ & PR+ cells detected in a breast cancer section.

Figure 2. Breast cancer biopsy section from 50 y/o female patient with metastatic invasive ductal adenocarcinoma, stained for EGFR. EGFR+ cells identified (drag slider to see segmentation of EGFR+ cells)

Quantification of Astrocyte Reactivity and Spatial Distribution in TBI-induced Rat Brain Tissue

Investigation of the activation of astrocytes within rat brain following mechanically induced severe traumatic brain injury (TBI) showed a significant increase in reactive astrocytes. Quantification of two parameters, the distance between neurons and nearest reactive astrocyte, and distance of reactive astrocytes to nearest blood vessel was conducted on rat brain sections labeled with GFAP. The average neuron-astrocyte distance found in control samples was consistent with reported results [2]. After mechanically induced traumatic brain injury, the distance between neurons and activated astrocytes was found to decrease in a significant manner. The astrocyte-blood vessel distance was found to increase due to increases to astrocyte activation and GFAP expression following TBI. A statistically significant increase in GFAP expression leading to a significant increase in the number of astrocytes detected following TBI, consistent with previously reported results [3].

Figure 3. Rat brain exposed to severe traumatic brain injury (TBI) via mechanical insult; tissue section labeled with IHC for GFAP, drag slider to visualize segmentation depicting astrocytes in red, and neurons in blue. Violin plot depicts distribution of the intensity of GFAP labeling in TBI vs control brain tissue sections.

Figure 4. Mechanically induced TBI in rat brain; representative region of IHC tissue section labeled with GFAP and nuclei labeled with hematoxylin, drag slider to reveal graphical representation of nearest neighbor analysis used to assess neuron-astrocyte distances. Violin-plot depicts distribution of neuron-astrocyte distances in TBI (reactive astrocytes) and control brain tissue. There was a statistically significant decrease in the average distance between neurons and reactive astrocytes measured from GFAP labeled sections.

Figure 5. Mechanically induced TBI in rat brain; representative region of IHC tissue section labeled with GFAP and nuclei labeled with hematoxylin, drag slider to reveal graphical representation of nearest neighbor analysis used to assess astrocyte-blood vessel distances. Violin-plot depicts distribution of reactive astrocyte-blood vessel distances in TBI and control brain tissue. There was a statistically significant increase in the average distance between astrocytes and nearest blood vessel measured from GFAP labeled sections, likely due to increased GFAP expression following TBI due to astrocyte activation, leading to increased number of astrocytes detected by GFAP labeling distal from blood vessels.

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References:

  1. Feldman, A.T., Wolfe, D. (June 2014). “Tissue Processing and Hematoxylin and Eosin Staining”. Histopathology. pp. 31-43.
  2. Distler, C., Dreher, Z., & Stone, J. (1991). Contact spacing among astrocytes in the central nervous system: an hypothesis of their structural role. Glia4(5), 484-494.
  3. Karve, I. P., Taylor, J. M., & Crack, P. J. (2016). The contribution of astrocytes and microglia to traumatic brain injury. British journal of pharmacology173(4), 692-702.

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