Image-based computational quantification and visualization of genetic alterations and tumour heterogeneity

Area of Science:

• Genomics and Computational Pathology
• Cancer Research
• Molecular Diagnostics

Background:

• Large-scale genome analyses reveal significant genetic alterations and tumour heterogeneity across various cancer types.
• Traditional fluorescence in situ hybridization (ISH) for assessing genetic copy-number variation (CNV) and heterogeneity is labor-intensive, has low throughput, and suffers from high inter-observer variability.

Purpose of the Study:

• To present an integrative, image-based computational workflow (ISHProfiler) for high-throughput and reproducible evaluation of tumour genetic alterations and heterogeneity.
• To enable accurate detection of molecular signals, objective quantification of CNV, and visualization of multi-level tumour heterogeneity.

Main Methods:

• Integration of bright-field dual-colour chromogenic and silver ISH assays with an image-based computational workflow (ISHProfiler).
• Application to diverse human tumours (prostate, endometrial, ovarian, gastric) using various tissue sizes and scanner types.
• Focus on quantifying heterogeneous genetic deletions (e.g., PTEN) and amplifications (e.g., 19q12, HER2).

Main Results:

• ISHProfiler facilitates accurate detection of molecular signals and high-throughput evaluation of CNV.
• The method provides expressive visualization of cellular, inter-tumour, and intra-tumour heterogeneity.
• Objective and reproducible quantification of heterogeneous genetic deletions and amplifications was achieved across different tumour types and sample preparations.

Conclusions:

• ISHProfiler offers an unprecedented throughput and reproducibility for assessing tumour genetic heterogeneity and CNV.
• This integrative computational approach overcomes limitations of traditional ISH, enabling more efficient and objective cancer molecular profiling.
• The method is robust across various tissue sizes and scanner types, making it broadly applicable in cancer research and diagnostics.