Multiomics Analysis Reveals Distinct Immunogenomic Features of Lung Cancer with Ground-Glass Opacity

Abstract

Rationale: Ground-glass opacity (GGO)-associated lung cancers are common and radiologically distinct clinical entities known to have an indolent clinical course and superior survival, implying a unique underlying biology. However, the molecular and immune characteristics of GGO-associated lung nodules have not been systemically studied. Objectives: To provide mechanistic insights for the treatment of these radiologically distinct clinical entities. Methods: We initiated a prospective cohort study to collect and characterize pulmonary nodules with GGO components (nonsolid and part-solid nodules) or without GGO components, as precisely quantified by using three-dimensional image reconstruction to delineate the molecular and immune features associated with GGO. Multiomics assessment conducted by using targeted gene panel sequencing, RNA sequencing, TCR (T-cell receptor) sequencing, and circulating tumor DNA detection was performed. Measurements and Main Results: GGO-associated lung cancers exhibited a lower tumor mutation burden than solid nodules. Transcriptomic analysis revealed a less active immune environment in GGO components and immune pathways, decreased expression of immune activation markers, and less infiltration of most immune-cell subsets, which was confirmed by using multiplex immunofluorescence. Furthermore, T-cell repertoire sequencing revealed lower T-cell expansion in GGO-associated lung cancers. HLA loss of heterozygosity was significantly less common in lung adenocarcinomas with GGO components than in those without. Circulating tumor DNA analysis suggested that the release of tumor DNA to the peripheral blood was correlated with the tumor size of non-GGO components. Conclusions: Compared with lung cancers presenting with solid lung nodules, GGO-associated lung cancers are characterized by a less active metabolism and a less active immune microenvironment, which may be the mechanisms underlying their indolent clinical course. Clinical trial registered with www.clinicaltrials.gov (NCT03320044).

Keywords: T-cell repertoire; circulating tumor DNA; genomics; ground-glass opacity; immune infiltration.

Figures

Figure 1.

Research strategy. (A) Description of sample collection and multiomics analysis. (B) Example axial CT images, 3D vascular reconstruction, and volumetric measurement for one nonsolid nodule (NSN) and one part-solid nodule (PSN) (50%). The ground-glass opacity components are equal to the NS divided by the TV. In B, the histologic features of nodules, including (a) an NSN of minimally invasive adenocarcinoma, (b) a PSN of minimally invasive adenocarcinoma, and (c) an SN of invasive adenocarcinoma, are shown Scale bars, 100 μm. 3D = three-dimensional; CT = computed tomography; NS = volume size of NSN; pts. = patients; S = volume size of solid component; SN = solid nodule; TCR = T-cell receptor; TV = total volume of lesion.

Figure 2.

Genomic landscape of lung adenocarcinoma with or without ground-glass opacity (GGO) components. (A) Top mutated cancer genes in at least three patients. Clinical features are listed at the bottom of the figure, and the number of mutated genes in each patient is shown at the top of the figure as red bars. The prevalence of mutated cancer genes in this cohort is represented as blue bars to the left of the figure. Patient PTHOG0047 with the highest tumor mutation burden in this cohort is detailed in the online supplement. (B) The association of the tumor mutation burden with low-grade (n = 11, 2.27 ± 1.19 Mut/Mb) versus intermediate or high-grade histology (n = 71, 5.74 ± 13.29 Mut/Mb) or (C) GGO status (NSN: n = 7, 1.85 ± 1.06 Mut/Mb; PSN: n = 23, 3.08 ± 1.27 Mut/Mb; SN: n = 52, 6.71 ± 15.44 Mut/Mb). N represents the sample size in each group, and the mean ± SD is also shown in brackets. (D) The incidence of commonly mutated cancer genes in lung adenocarcinomas with different proportions of GGO components (grouped as quartiles). For box plots within violin plots, each box indicates the first quartile (Q1) and third quartile (Q3), and the black horizontal line represents the median; the upper whisker is the min[max(x), Q3 + 1.5 × IQR], and the lower whisker is the max[min(x), Q1 − 1.5 × IQR], where x represents the data, Q3 is the 75th percentile, Q1 is the 25th percentile, and IQR = Q3 − Q1. The widths of the violin plots indicate the kernel density of the data. CNV = copy number variation; IQR = interquartile range; LPA = lepidic-predominant invasive adenocarcinoma; max = maximum; MIA = minimally invasive adenocarcinoma; min = minimum; Mut = mutations; NSN = nonsolid nodule; PSN = part-solid nodule; SN = solid nodule; SV = structural variation.

Figure 3.

The association of the immune contexture derived from RNA sequencing with different ground-glass opacity (GGO) statuses in lung adenocarcinomas. (A) Heatmap of normalized enrichment scores for infiltration of 28 immune cells. The upper panel represents the expression of cytolytic activity, PRF1, GZMA, CD8, and IFNG. Patients’ features, including smoking, stage, GGO status (red, solid nodule [SN] with no GGO; blue, nonsolid nodule [NSN] + part-solid nodule [PSN]), and the GGO-component percentage (indicated as color scales), are listed. (B) Expression of immune markers as determined by using RNA-sequencing data (14 NSN/PSN cases vs. 37 SN cases). The expression levels were 3.43 ± 0.73 versus 4.18 ± 0.76 log2 (transcripts per million [TPM] + 1) for CD8A, 0.59 ± 0.44 versus 1.31 ± 0.97 log2 (TPM + 1) for IFNG, and 4.23 ± 0.58 versus 4.80 ± 0.72 log2 (TPM + 1) for cytolytic activity. (C) Volcano plot of differentially expressed genes comparing SNs with NSNs/PSNs. Red dots and green dots indicate significantly upregulated and downregulated genes in NSN and PSNs, respectively. (D) Comparisons of the NSNs/PSNs with SNs for different immune cells (14 NSN/PSN cases vs. 37 SN cases). The measures of infiltration were 0.20 ± 0.85 versus 0.30 ± 0.09 for activated CD4 T cells, 0.46 ± 0.06 versus 0.51 ± 0.06 for activated CD8 T cells, 0.40 ± 0.06 versus 0.45 ± 0.09 for regulatory T cells, and 0.01 ± 0.06 versus −0.03 ± 0.07 for eosinophils. (E) Representative images from patients with NSNs and SNs for CD3+ T cells (magenta), CD4+ T cells (green), CD8+ T cells (red), FoxP3+ regulatory T cells (cyan), and DAPI (blue), as determined by using multiplex immunofluorescence staining. Scale bars, 100 μm. FDR = false discovery rate; MDSC = myeloid-derived suppressor cell.

Figure 4.

T-cell clonality (left), diversity (middle), and the proportion of the top 10 clones (right) in (A) nonmalignant nodules versus lung adenocarcinoma (LUAD) tissues with ground-glass opacity (GGO) components (NSNs/PSNs) or without GGO components (SNs) and (B) peripheral blood mononuclear cell (PBMCs). (C) Shared T-cell clones in LUAD specimens and PBMCs as quantified by using the MOI. (D) For each patient, the HLA heterozygote status and data on whether HLA-A/B/C kept or lost alleles are listed. The right bar represents the number of patients in whom HLA loss of heterozygosity (LOH) events on related HLA genes occurred. (E) Numbers of patients with HLA LOH events (left panel) and an HLA homozygous status (right) among patients with LUAD with a GGO component versus without a GGO component. P values as calculated by using the chi-square test and ORs are shown. (F) The incidence of HLA LOH events in LUADs with different proportions of GGO components (grouped as quartiles). MOI = Morisita overlap index; NSN = nonsolid nodule; OR = odds ratio; PSN = part-solid nodule; SN = solid nodule.

Figure 5.

Cell-free DNA (cfDNA) mutations in patients with lung adenocarcinoma with clinicopathologic features. (A) The number of variations from tissue and plasma, the VAF of driver genes detected from plasma, and clinical features in 82 patients with lung adenocarcinoma are listed. (B) The cfDNA concentration of nonmalignant lung nodules versus lung cancers presenting as SNs or NSNs/PSNs. Numbers of patients (C) with versus without GGO component and (D) with adenocarcinoma versus with nonadenocarcinoma. (E) The solid volume in circulating tumor DNA (ctDNA)-positive versus ctDNA-negative nodules. For all box plots or box plots within violin plots, each box indicates the first quartile (Q1) and third quartile (Q3), and the black horizontal line represents the median; the upper whisker is the min[max(x), Q3 + 1.5 × IQR], and the lower whisker is the max[min(x), Q1 − 1.5 × IQR], where x represents the data, Q3 is the 75th percentile, Q1 is the 25th percentile, and the IQR = Q3 − Q1. The widths of violin plots indicate the kernel density of the data. GGO = ground-glass opacity; IQR = interquartile range; LPA = lepidic-predominant invasive adenocarcinoma; max = maximum; MIA = minimally invasive adenocarcinoma; min = minimum; NSN = nonsolid nodule; PSN = part-solid nodule; SN = solid nodule; SNV = single-nucleotide variant; VAF = variant allele frequency.

Figure 6.

Integrated genomic and immune features across patients with lung adenocarcinoma with different GGO components. ctDNA = circulating tumor DNA; CYT = cytologic activity; GGO = ground-glass opacity; LOH = loss of heterozygosity; MUT = mutation; NSN = nonsolid nodule; PSN = part-solid nodule; SN = solid nodule; TMB = tumor mutation burden.