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Review
. 2023 Jul;6(7):e1796.
doi: 10.1002/cnr2.1796. Epub 2023 Feb 22.

Artificial intelligence and digital biomarker in precision pathology guiding immune therapy selection and precision oncology

Ralf Huss  1   2 , Johannes Raffler  2 , Bruno Märkl  1
Affiliations
Review

Artificial intelligence and digital biomarker in precision pathology guiding immune therapy selection and precision oncology

Ralf Huss et al. Cancer Rep (Hoboken). 2023 Jul.

Abstract

Background: The currently available immunotherapies already changed the strategy how many cancers are treated from first to last line. Understanding even the most complex heterogeneity in tumor tissue and mapping the spatial cartography of the tumor immunity allows the best and optimized selection of immune modulating agents to (re-)activate the patient's immune system and direct it against the individual cancer in the most effective way.

Recent findings: Primary cancer and metastases maintain a high degree of plasticity to escape any immune surveillance and continue to evolve depending on many intrinsic and extrinsic factors In the field of immune-oncology (IO) immune modulating agents are recognized as practice changing therapeutic modalities. Recent studies have shown that an optimal and lasting efficacy of IO therapeutics depends on the understanding of the spatial communication network and functional context of immune and cancer cells within the tumor microenvironment. Artificial intelligence (AI) provides an insight into the immune-cancer-network through the visualization of very complex tumor and immune interactions in cancer tissue specimens and allows the computer-assisted development and clinical validation of such digital biomarker.

Conclusions: The successful implementation of AI-supported digital biomarker solutions guides the clinical selection of effective immune therapeutics based on the retrieval and visualization of spatial and contextual information from cancer tissue images and standardized data. As such, computational pathology (CP) turns into "precision pathology" delivering individual therapy response prediction. Precision Pathology does not only include digital and computational solutions but also high levels of standardized processes in the routine histopathology workflow and the use of mathematical tools to support clinical and diagnostic decisions as the basic principle of a "precision oncology".

Keywords: artificial intelligence; decision support; digital biomarker; immune oncology; precision pathology.

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Conflict of interest statement

The authors have stated explicitly that there are no conflicts of interest in connection with this article.

Figures

FIGURE 1
FIGURE 1
Simplified scheme of the proposed path from a regular diagnostic pathology workflow to delivering a precision oncology approach through the AI‐supported application of digital biomarker that allow the best possible response prediction of immune therapies.
See this image and copyright information in PMC

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