Additional file 1 of Spatial tumour gene signature discriminates neoplastic from non-neoplastic compartments in colon cancer: unravelling predictive biomarkers for relapse
Creators: name: Sallinger, Katja
name: Gruber, Michael
name: Müller, Christin-Therese
name: Bonstingl, Lilli
name: Pritz, Elisabeth
name: Pankratz, Karin
name: Gerger, Armin
name: Smolle, Maria Anna
name: Aigelsreiter, Ariane
name: Surova, Olga
name: Svedlund, Jessica
name: Nilsson, Mats
name: Kroneis, Thomas
name: El-Heliebi, Amin
Publisher: name: figshare
Year: 2024
Subjects: subject: Space Science
subject: Medicine
subject: Microbiology
subject: FOS: Biological sciences
subject: Genetics
subject: Molecular Biology
subject: Biotechnology
subject: Chemical Sciences not elsewhere classified
subject: Biological Sciences not elsewhere classified
subject: Information Systems not elsewhere classified
subject: Cancer
subject: Plant Biology
subject: Virology

description: Additional file 1: Table S1: List of clinical data. Table S2: List of designed gene panel. Table S3: Quality control of in situ sequencing data. The list contains the number and percentages of expected reads, unexpected reads and homomers of each sample calculated with a threshold of 0.1 from the MATLAB script (see methods section). Table S4: Parameter values used for microscope images of size (7660px, 7700px). Table S5: The resulting p-values for the statistical testing of relapse and non-relapse patients with the neoplastic tissue compartments. Method S1: virtual H&amp;E image. Method S2: Compartment building by morphology. Method S3: Compartment building by gene expressions. Method S4: Gene set selection. Method S5: Gene counting in the compartments. Method S6: Excluding areas. Method S7: Statistical testing. Fig. S1: a) DAPI-stained image, b) FITC-stained image used for calculating and c) virtually stained H&amp;E image of the tissue sample. Fig. S2: a) The tissue areas in the tissue sections as classified by a pathologist: red–neoplastic tissue, green–non-neoplastic tissue. The blue area marks a region that was excluded from the analysis due to high autofluorescence or lost tissue during hybridisation. The derived representative binary tissue compartment (TC) b) for the neoplastic and c) for the non-neoplastic tissue. d) The calculated TC combined in one image with the previously described colour coding. Fig. S3: Schematic example for the uniform kernel. Fig. S4: The density plots a) for FLT4, b) for BIK, c) for EREG and d) for MET. The areas with high density values (light red and yellow area) in b)-d) correlate with the areas of neoplastic tissue. Fig. S5: a) With the gene set S = {BIK, CCND1, CD44, EREG, ITGAV, MET, MYBL2, S100A4}, referred to as tumour gene signature, calculated tissue compartment for the neoplastic tissue. b) Hybridisation area compartment defined through a disk of radius centered in the middle of image. Fig. S6: Binary tissue compartments (TC) a) for all cells and b) for all ISS genes . c) The composite TC and d) the calculated representative non-neoplastic TC. Fig. S7: The calculated tissue compartments (TC) combined in one image: red–neoplastic TC and green–non-neoplastic TC. Fig. S8: The overlap (dark red) between the neoplastic tissue compartment (TC): dark red–overlap, light red–morphological-based TC with no overlap and pink–gene expression-based TC with no overlap. Fig. S9: Tissue damage (red) of patient sample 7 during the sequencing procedure. a) Virtually converted H&amp;E staining of the sample. Image of tissue after b) the third c) the fourth and d) the fifth sequencing cycle. e) Shows the neoplastic and non-neoplastic compartments that were generated based on gene expression with the excluded area in blue. Tissue damage was observed after sequencing cycle 3-5. The red marked area had to be excluded from further analysis. Fig. S10: Highly autofluorescent areas observed in patient sample 6 (red) that showed higher pixel intensity values than truly positive signals were excluded from further analysis. a) Virtually converted H&amp;E staining of the sample. b) Highly autofluorescent region was marked in red. c) Shows the neoplastic and non-neoplastic compartments that were generated based on gene expression with the excluded area in blue. Fig. S11: Alignment of spots: Alignment performed in CellProfiler by using ImageJ plugins MultiStackReg, StackReg and TurboReg. The figure shows a) correctly aligned spots and b) wrongly aligned spots. Fig. S12: Comparison of spatial analysis vs. bulk analysis: Volcano plots with a significance level α=0.05 of significantly upregulated genes in a) the neoplastic tissues compartment and b) the total tissue area of relapsed patients in comparison to non-relapsed patients. Fig. S13: Spatial distribution of 176 ISS detected transcripts.