CISH App explained

Chromogenic in situ hybridization (CISH) is used to detect specific DNA or RNA sequences in tissue samples. It uses enzyme-based staining rather than fluorescence (FISH), allowing for high-resolution imaging, quantification, and analysis under standard, bright-field microscopes. CISH uses labeled probes (complementary DNA or RNA) that bind to target sequences, followed by a peroxidase or alkaline phosphatase reaction to create a colorimetric signal.

CISH Colors

The typical colors used to visualize gene probes are red and blue (often resulting in dark blue/purple or black precipitates), or a combination of red and green. 

• Red: Produced by substrates like Fast-Red (alkaline phosphatase – AP).
• Blue/Dark Blue: Produced by substrates like blue cyanine dye (horseradish peroxidase – HRP).
• Black/Dark Brown: Often produced by 3,3′-diaminobenzidine (DAB) or silver-enhanced in situ hybridization (SISH) for high-contrast, stable, and dense signals.
• Green: Can be used in dual-color, often created from fluorescent signals converted to chromogenic, or through specific enzyme substrates. 

Counter-stain: hematoxylin is a typical counter-stain to make the cells more visible

How to create a custom CISH color scheme

In MIKAIA’s CISH App, the user can easily set up their own color assays in 2 steps:

Step 1: create new Assay

create new assay (e.g. “red-blue”) and add one “gene” per probe, specify a name and use the color picker to pick the probe color directly in your slide. The second color per gene is used to draw the spots – by default the inverse color is used to ensure good contrast.

The “Spot detection sensitivity” parameter influences whether only very distinct (low sensitivity) or also fainter spots (high sensitivity) are detected. The algorithm first detects any spots, regardless of the color. Therefore, this parameter applies to all genes.

All detected spots are then assigned to a gene based on their color. Next, spots with a too low intensity can be discarded. The “Req. intensity” parameter (per gene) specifies the minimally required intensity.

Lastly, all remaining spots are visualized and the gene-to-cell mapping is computed (stored in hdf5 inside the MIKAIA *.ano file).

Step 2: configure CISH ratio

Cells can optionally be graded into 3 classes based on the contained genes ratio or copy numbers:

The above configuration reads:

• classify as “positive“: all cells with a black/red ratio >= 2.0 or that contain at least 6 copies of “black”
• classify as “equivocal“: all cells with a black/red ratio >= 2.0 or that contain 4 or 5 copies of “black”
• classify as “negative“: all other cells

CISH results diagrams

A set of diagrams illustrate different aspects of the results.

• Copy numbers scatter plot: is a 2D historgam that shows the percentage of cells for each combination of copy numbers of 2 genes
• Ratio: <gene 1> / <gene 2>: this vertical bar plot is a histogram where each bin represents a FISH ratio window and the bar height indicates the number of cells that fall into this FISH ratio window.
• Copy numbers histogram: is a grouped vertical bar plot where each bar indicates the number of cells with the given copy count.
• Cell scatter plot: plots 2 cell attributes against each other, e.g. the counter stain intensity and area

Below the diagrams, the tables “Cells by grade” and “CISH spots” list the numerical results. “Filtered cells” shows how many cells identified by the AI have been discarded due to the user-specified filter settings.

As will all MIKAIA apps, all numerical results can be exported into a CSV table.