Delineation of cell subpopulations and cell-cell interactions to determine correlations between drug response and tumor microenvironment in early-stage lung cancer
The tumor microenvironment (TME) is an integral player in cancer initiation, tumor progression, response and resistance to anti cancer therapy. Understanding the complex interactions of tumor immune architecture has therefore become increasingly desirable to guide patient selection. Conventional studies that underestimate the potential value of the spatial architecture of the TME are unable to completely elucidate its complexity. To overcome these limitations, we used quantitative image analysis based on multiplexed immunohistochemistry and deep learning technologies to interrogate complex information from the tumor microenvironment and find predictive insights into treatment response for non small cell lung cancer.
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