Immune checkpoint inhibitors (ICI) have improved survival in a subset of patients with metastatic non-small cell lung cancer (NSCLC). However, most patients develop resistance to these therapies, and there is little insight into how this happens or how best to combat this clinically. Previous studies have implicated deficiencies in chromosomal stability or DNA damage repair (DDR) in both ICI resistance and sensitivity. Our preliminary data have identified a possible role for DDR and chromosomal instability in ICI resistance, and we have developed novel strategies to identify these processes from resistance biopsies. However, how these mutations may affect anti-tumor immunity, and how the tum...

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Immune checkpoint inhibitors (ICI) have improved survival in a subset of patients with metastatic non-small cell lung cancer (NSCLC). However, most patients develop resistance to these therapies, and there is little insight into how this happens or how best to combat this clinically. Previous studies have implicated deficiencies in chromosomal stability or DNA damage repair (DDR) in both ICI resistance and sensitivity. Our preliminary data have identified a possible role for DDR and chromosomal instability in ICI resistance, and we have developed novel strategies to identify these processes from resistance biopsies. However, how these mutations may affect anti-tumor immunity, and how the tumor and immune system coordinate to drive ICI resistance, has not been fully studied. In this proposal, we aim to address these questions by sequencing a rich dataset of pre- and post-resistance tumor specimens. In our first aim, we will analyze the genomic data to identify subclones that drive ICI resistance. We will determine whether DDR defects seem to be driving these subclones, and infer why they contribute to resistance by investigating associated mutations and whether these cause tumors to become less immunogenic. In the second aim, we will develop new methods to identify these tumor subclones within tumor expression data on a histologic slide (spatial transcriptomics), allowing us to determine how these tumor subclones are organized spatially. Finally, in the third aim, we will use this spatial transcriptomics platform to identify how tumor subclones interact with the neighboring immune cells, focusing on whether there are immune cells enriched in resistance samples and how these cluster with tumor subclones. We believe that the innovative research outlined in this proposal will illuminate the biological basis of resistance to ICI, helping to inform efforts to develop new drugs and identify strategies to avoid resistance, therapy improving the lives of cancer patients.

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