bioRxivCancer BiologyPreprint
A Spatial Proteomic Atlas of Tertiary Lymphoid Structures in Non-Small Cell Lung Cancer Identifies a Novel Predictive Class of Lymphoid Aggregates
Tyler RisomiD, Rajiv JesudasoniD, Evan LiuiD, Andrew Hill, Niha G. BeigiD, Conrad FooiD, Ouida Liu, Eloisa Fuentes, Lisa TaiiD, Kedar Prasad, Jennifer Giltnane, Robert J. JohnstoniD, Lisa M. McGinnisiD
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Abstract
Tertiary lymphoid structures (TLS) predict benefit from immune checkpoint inhibitors (CPIs), yet mature, germinal-center-rich TLS are infrequent in solid tumors by histological review. Here, using 38-plex MIBI spatial proteomics across 165 lymphoid structures from 14 NSCLC resections, we establish a continuum of TLS maturity using high dimensional compositional, spatial, and molecular features. We demonstrate that histologically-defined lymphoid aggregates (LA) comprise a heterogeneous class of structures, which span this continuum of maturity. We identify a subset of lymphoid aggregates that harbor follicular dendritic cell networks, T follicular helper cells, and activated B cell states characteristic of mature TLS, yet are not readily distinguished from other LA structures in our histological review. We developed a novel digital pathology classifier to identify mature LAs in CPI trials, and demonstrate in a retrospective analysis of Atezolizumab in advanced NSCLC that the inclusion of mature LAs greatly expands the biomarker-eligible population while maintaining strong predicted benefit. Together, these data redefine the biological spectrum of tumor-associated lymphoid aggregates and provide a framework for implementing maturity-informed TLS biomarker strategies.
- organism: human
- assay: spatial transcriptomics
- assay: proteomics
- research focus: cell type annotation
- research focus: clustering
- research focus: benchmarking
- approach: deep learning
- approach: statistical model
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