Single-Cell Analysis in Immuno-Oncology.

Area of Science:

• Oncology
• Immunology
• Genomics

Background:

• Tumor microenvironments (TME) exhibit significant patient-to-patient variability, influencing immunotherapy response.
• Understanding TME complexity is crucial for tailoring cancer treatments and improving patient outcomes.
• Single-cell (sc) omics technologies offer unprecedented resolution for dissecting TME heterogeneity.

Purpose of the Study:

• To review recent advancements in multi-omics profiling for high-throughput assessment of TME at single-cell resolution.
• To highlight how scRNA-seq, scATAC-seq, and scTCR-seq enhance comprehension of adaptive immune responses in cancer.
• To identify potential therapeutic targets and biomarkers for personalized cancer immunotherapy.

Main Methods:

• Utilizing single-cell RNA sequencing (scRNA-seq) to analyze gene expression in individual cells.
• Employing assay for transposase-accessible chromatin with sequencing (scATAC-seq) to study chromatin accessibility.
• Leveraging T-cell receptor sequencing (scTCR-seq) to characterize T-cell clonotypes and immune checkpoints.
• Integrating mass, tissue-based, or microfluidics cytometry with bioinformatics tools for comprehensive TME analysis.

Main Results:

• Multi-omics profiling provides high-throughput assessment of analytes at single-cell resolution.
• Characterization of T-cell receptor (TCR) clonotypes and immune checkpoints offers insights into adaptive immunity.
• Detailed analysis of immune and non-immune cell subsets within the TME reveals response or resistance mechanisms.
• Identification of diverse cellular and non-cellular components influencing disease progression and treatment efficacy.

Conclusions:

• Deciphering TME diversity through single-cell multi-omics is key to personalized cancer immunotherapy.
• Understanding immune cell dynamics, antigen specificity, and checkpoints informs therapeutic strategies.
• Future integration of high-dimensional and spatial data will enable novel multi-modal biomarkers for treatment selection and monitoring.