Multidimensional quantitative characterization of the tumor microenvironment by multicontrast nonlinear microscopy

Area of Science:

• Biomedical Optics
• Cancer Research
• Pathology

Background:

• Tumor microenvironment characterization is crucial for diagnosis but challenging in complex biological systems.
• Nonlinear optical imaging offers a promising approach for analyzing tissue properties.
• Simultaneous acquisition of multiple tissue features from unperturbed samples is needed.

Purpose of the Study:

• To develop and validate a nonlinear effects-based multidimensional optical imaging platform.
• To simultaneously capture contrasting nonlinear optical signatures from human skin tissues.
• To analyze morphological and metabolic differences in skin tissues for cancer diagnosis.

Main Methods:

• Developed a super-multiplex nonlinear optical imaging system.
• Applied the platform to freshly excised human skin tissues.
• Performed qualitative and quantitative analysis of autofluorescence (FAD), collagen, lipids, and proteins.

Main Results:

• Successfully captured and analyzed multiple nonlinear optical signatures (autofluorescence, collagen, lipids, proteins).
• Illustrated morphological and metabolic differences between epidermis and dermis in various skin cancer types.
• Demonstrated stain-free histological findings complementing H&E staining for basal cell carcinoma and pigmented nevus.

Conclusions:

• The platform efficiently classifies skin carcinoma subtypes using multi-parameter, stain-free analysis.
• Endogenous molecules can be translated into biomarkers for rapid cancer screening.
• This approach shows potential for improved intraoperative diagnosis and pathological assessment.