Abstract
The tumor microenvironment (TME) cells interact with each other and play a pivotal role in tumor progression and treatment response. A comprehensive characterization of cell and intercellular crosstalk in the TME is essential for understanding tumor biology and developing effective therapies. However, current cell infiltration analysis methods only partially describe the TME's cellular landscape and overlook cell-cell crosstalk. Here, this approach, CITMIC, can infer the cell infiltration of TME by simultaneously measuring 86 different cell types, constructing an individualized cell-cell crosstalk network based on functional similarities between cells, and using only gene transcription data. This is a novel approach to estimating the relative cell infiltration levels, which are shown to be superior to the current methods. The TME cell-based features generated by analyzing melanoma data are effective in predicting prognosis and treatment response. Interestingly, these features are found to be particularly effective in assessing the prognosis of high-stage patients, and this method is applied to multiple high-stage adenocarcinomas, where more significant prognostic performance is also observed. In conclusion, CITMIC offers a more comprehensive description of TME cell composition by considering cell-cell crosstalk, providing an important reference for the discovery of predictive biomarkers and the development of new therapeutic strategies.