Abstract 488P
Background
Clinical investigations have great interest in understanding how ground-glass opacities (GGO) evolve into solid nodular lung adenocarcinoma (LUAD). However, there exists a dearth of research on ecosystem-level dynamics. Comprehensive insights into this phenomenon hinge on patient biopsies, which, when coupled with advanced single cell studies, hold the potential to unravel the intricacies of GGO progression and its transition into solid nodular LUAD.
Methods
We implemented a machine-learning framework to analyze scRNA-seq and WGS data derived from 55 patients stratified based on radiological patterns. In combination with in situ multiplex IF and HLA-immunopeptidome, we analysed the immune-ecosystem associated neoantigen presentation, followed by validation with HLA-tetramer CD8 T cell assay. Based on these methods, we consequently refined early-stage LUAD classification.
Results
We defined six lung immune multicellular ecotypes (LIMEs), in which two cancer cell state-associated LIMEs were implicated in distinct radiological patterns. These early stage malignant cells, through presenting GGO-associated neoantigens, were recognized by CXCL13+ CD8 T cells that formed an anti-tumoral LIME with other stromal cells. Solid nodular specific LIMEs, containing CTHRC1+ CAFs, SPP1+ TAMs and BANK1+ B cells, through inter-ecotype interactions, drove CD8 T cell exhaustion, leading to tumour progression.
Conclusions
This work offers an ecosystem-level portrayal of early-stage LUAD. It furnishes a resource for delving into the pre-malignant transformation of lung epithelium and its associated microenvironment. It outlines both intrinsic and extrinsic mechanisms that underpin the emergence of GGO and subsolid patterns. It imparts biological rationales as to select patients with early-stage LUAD might benefit from perioperative adjuvant therapies.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
West China Hospital, Sichuan University, Chengdu, China.
Funding
National Science Fondation of China.
Disclosure
The author has declared no conflicts of interest.
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