Neoadjuvant Botensilimab/ Balstilimab for localized mismatch repair proficient and deficient colon cancer: Results of the NEST phase 2 clinical trial
Intensity values for each sample can be downloaded from GEO: GSE337193.
| Sample_name | ROI | MSI | Naming in figures |
|---|---|---|---|
| NEST2-06 | tumor_bed | Stable | NEST2-06_Resection |
| NEST1-06 | tumor_bed | High | NEST1-06_Resection |
| NEST1-11 | tumor | Stable | NEST1-11_Baseline |
| NEST1-04 | tumor | Stable | NEST1-04_Baseline |
| NEST1-05 | tumor | High | NEST1-05_Baseline |
| NEST1-05 | tumor_bed | High | NEST1-05_Resection |
| NEST2-04 | tumor | Stable | NEST2-04_Baseline |
| NEST1-04 | tumor | Stable | NEST1-04_Resection |
| NEST1-01 | tumor_bed | Stable | NEST1-01_Resection |
| NEST2-03 | tumor_bed | Stable | NEST2-03_Resection |
| NEST1-08 | tumor_inner | Stable | NEST1-08_Resection |
| NEST1-11 | tumor_bed | Stable | NEST1-11_Resection |
| NEST2-06 | tumor | Stable | NEST2-06_Baseline |
| NEST2-08a | tumor | Stable | NEST2-08a_Baseline |
| NEST2-01 | tumor_bed | Stable | NEST2-01_Resection |
| NEST2-04 | tumor_inner | Stable | NEST2-04_Resection |
| NEST2-10 | tumor_inner | Stable | NEST2-10_Resection |
Immunofluorescence intensity values were extracted from TIFF images using HALO software for selected ROIs. Mean nuclear intensity values were used for the protein markers FOXP3, PCNA, PAX5, and MKI67, while mean cytoplasmic intensity values were used for the remaining markers. This produced one table per Sample_name, from which we proceeded as follows:
- Step 1: QC, normalization and probes poisitivity assesment. From single cell intensity values, exclude cells with the lowest 2% of Area and 2% of DAPI signal. Then for each ROI/probe, generate a binary expression matrix following the 6σ approach. QC. We will run this script for each sample_name/ROI of interest.
- Step 2: cell annotation. Using the binary matrix, annotate cells on the positivity of certain markers (probes), and the negativity of the rest of the markers. In a second round of annotation, use VIMENTIN, Podoplanin and SMA probes as neutral probes, so any of the cells can be positive for them. cell_typing. We will run this script for each sample_name/ROI of interest.
- Step 3: cell type characterization and niche identification. Characterization of cell type composition in each ROI and identification of cellular niches across all ROI. ROI_characterization
- Step 4: cell type density differences. With the cell type annotation, normalize cell type counts based on the area of each ROI and apply t-test for each cell type to identify cell type density differences between conditions. abundances
- Step 5: immune proportion differences. Calculate immune proportions within each sample and apply t-test to identify immune differences between conditions. immune_diff
- Step 6: neighborhood analysis. Neighborhood analysis to look for differences in the proportion of the different cell types within 50 microns of each cell within the cell type of interest between condtions. neighborhood