Eco-Evolutionary Guided Pathomic Analysis Detects Biomarkers to Predict Ductal Carcinoma In Situ Upstaging.

Area of Science:

• Oncology
• Cancer Biology
• Ecology

Background:

• Cancers evolve within a dynamic tumor microenvironment.
• Ductal carcinoma in situ (DCIS) requires biomarkers to predict progression to aggressive disease.

Purpose of the Study:

• To investigate the predictive power of hypoxia and acidosis biomarkers for DCIS upstaging using an ecological framework.
• To develop novel biomarkers for predicting aggressive breast cancer progression.

Main Methods:

• Quantitative analysis of immunohistological images from DCIS biopsy specimens.
• Development of an eco-evolutionary approach to define tumor microenvironment habitats based on oxygen diffusion.
• Identification of hypoxia-responding (CA9+) and acid-adapted (LAMP2b+) cancer cell phenotypes.
• Spatial pattern analysis of biomarker distribution to characterize tumor niches.
• Random forest classifier with 5-fold validation for outcome prediction.

Main Results:

• Ecological analysis of hypoxia and acidosis biomarkers significantly improved prediction of DCIS upstaging compared to traditional methods.
• Specific spatial patterns of biomarkers within tumor niches predicted patient upstaging.
• The random forest classifier achieved an AUC of 0.74 for predicting clinical outcome.

Conclusions:

• Tumor ecological features are critical for biomarker discovery in cancer evolution.
• An eco-evolutionary approach offers a powerful strategy for identifying biomarkers to predict DCIS progression and clinical outcomes.