Multiomics analysis reveals a distinct response mechanism in multiple primary lung adenocarcinoma after neoadjuvant immunotherapy

Abstract

Multiple primary lung cancer (MPLC) remains a tough challenge to diagnose and treat. Although neoadjuvant immunotherapy has shown promising results in early stage non-small cell lung cancer, whether such modality can benefit all primary lesions remains unclear. Herein, we performed integrated multiomics analysis in one patient with early stage MPLC with remarkable tumor shrinkage in a solid nodule and no response in two subsolid nodules after treatment with three cycles of neoadjuvant pembrolizumab. Genomic heterogeneity was observed among responding nodules with high levels of infiltrating CD8⁺ and CD68⁺ immune cells. Substantially downregulated human leukocyte antigen (HLA)-related genes and impaired T lymphocyte function were observed in non-responding nodules. A larger proportion of infiltrating tissue resident memory T cells (Trm) along with high T cell receptor repertoire clonality in responding nodules were validated as predictive and prognostic biomarkers in multiple cancer types using external public datasets. These results suggested that neoadjuvant programmed death 1 (PD-1)/programmed death ligand 1 inhibitors alone may not be an optimal therapeutic strategy for MPLC due to disparities in genomic alterations and immune microenvironment among different lesions. Additionally, we postulate that increased infiltration of Trm may be a unique marker of early immune responses to PD-1 blockade.

Keywords: immunotherapy; lung neoplasms; translational medical research; tumor biomarkers; tumor microenvironment.

Figure 1

Patient clinical and pathological evaluation following neoadjuvant immunotherapy. (A) Radiological evaluation of three resected nodules after three cycles of neoadjuvant immunotherapy showing notable tumor shrinkage of the solid nodule; however, the other nodules remained stable. (B) Comprehensive pathological evaluation integrated with mIHC of three surgically resected nodules. The extent of staining and the percentage of Foxp3-positive cells with nucleus staining are listed on the lower left corner of each slide. mIHC and PD-L1 images using the Dako 22C3 assay of nodules are obtained. mIHC panels are displayed in color on the lower right corner of the IHC slides: CD8 (white), CD56 (purple), CD68 (red), HLA-DR (green); PANCK (cyan). The expression level of PD-L1 is listed on the lower right corner of IHC slides. CNV, copy number variation; HLA, human leukocyte antigen; IC, immune cell: mIHC, multiplex immunohistochemistry; PD-L1, programmed death ligand 1; PR, partial response; RECIST, Response Evaluation Criteria in Solid Tumors; SD, stable disease; TMB, tumor mutation burden; TTF-1, thyroid transcription factor 1.

Figure 2

Heterogeneity of multiple primary lung cancer (MPLC) and single-cell RNA sequencing (scRNA-seq) analysis of differentially enriched pathways. (A) Genomic alteration of MPLC and somatic copy number variants. Bar chart on the right shows genomic instability, tumor mutation burden (TMB) and ploidy for each corresponding lesion. (B) A Venn diagram showing highly inconsistent human leukocyte antigen (HLA) types among nodules. (C) Stacked column chart of CDR3 frequency among nodules highlighting high frequency of CDR3 alignment in responding nodules. (D) Shannon index and CDR3 clonality of T cell receptor repertoire. (E) A volcano plot of differentially expressed genes between W2 and W1/W3 cancer cells (EPCAM+) with immune modulation (red) and tumor growth (blue) associated genes highlighted in corresponding color. (F) Gene set enrichment analysis (GSEA) between W2 and W1/W3 cancer cells among four cancer-related pathways, including fatty acid metabolism, epithelial mesenchymal transition, hypoxia-regulated genes and G2/M checkpoint. (G) Gene Ontology (GO) analysis of differentially enriched biological processes between W2 (red) and W1/W3 (blue) cancer cells.

Figure 3

Diverse differentiation trajectories of CD8⁺ T lymphocytes and prognostic value of tissue resident memory T cells (Trm). (A) UMAP projection of 2755 CD8⁺ T lymphocytes from three nodules clustered into nine groups by feature markers. (B) Heatmap of average gene expression value of immune checkpoint and costimulation-related genes among different CD8 T clusters. (C) Pseudo-time analysis of six major CD8⁺ T lymphocyte clusters showing two differentiation trajectory fates. (D) Radiation plot showing significant differential expression for each fate. Highly expressed genes are colored in red and genes with low expression in blue. Bar charts on the right indicate highly involved processes in fate 1 (orange) and fate 2 (blue), respectively. (E) Confirmation of the predictive and prognostic value of the Trm signature using external validation cohorts including two TCGA datasets and three retrospective studies. Log-rank p value is presented for each independent survival analysis. TCGA, The Cancer Genome Atlas; UMAP, Uniform manifold approximation and projection.