Assessment and evaluation of heterogeneity in data from immune infiltration spatial niches in lung cancer

Sammanfattning: The protein biomarker expressions in three types of sampled immune INFILTration spatial niches in lung cancer tissue were measured using the new technology Digital Spatial Profiler (DSP). The three types of immune INFILTration that were observed in lung tumors were STROMA identified as immune cells separate from tumor cells, Tertiary lymphoid structures (TLS) identified as dense structures of organized immune cells and finally Infiltraterate where immune cells dispersed among and in direct contact with tumor cells (INFILT). The pairwise inter and intra-patient correlation between the protein biomarkers were evaluated using the Bland- Altman methods for Calculating correlation coefficients with repeated observations. The result showed that the absolute value of the inter- patient correlation levels were higher for sample type INFILT compared to STROMA while the absolute value of the intra- patient correlation levels were slightly higher between the biomarkers of the sample type STROMA. In order to investigate added value of sampling multiple regions from individual tumors, the intra- patient heterogeneity of the protein markers in the three different spatial niches were evaluated. To this end, three different estimators were used: standard deviation, median absolute deviation and range. After comparing the results, it was concluded that standard deviation was the preferred method. Since it is applied on the complete set of available data and captures the behavior of the tail of the data which is desirable for our purpose. The mean squared error in the ANOVA table, with the patients identity as the independent variable and marker values for each sample type as the dependent variable was calculated as a measure of heterogeneity of the markers within patients.