Increased inflammatory signature in myeloid cells of non-small cell lung cancer patients with high clonal hematopoiesis burden

  1. Hyungtai Sim
  2. Hyun Jung Park
  3. Geun-Ho Park
  4. Yeon Jeong Kim
  5. Woong-Yang Park
  6. Se-Hoon Lee  Is a corresponding author
  7. Murim Choi  Is a corresponding author
  1. Department of Biomedical Sciences, Seoul National University College of Medicine, Republic of Korea
  2. Samsung Genome Institute, Samsung Medical Center, Republic of Korea
  3. Research Institute for Veterinary Science, College of Veterinary Medicine, Seoul National University, Republic of Korea
  4. Samsung Genome Institute, Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Republic of Korea
  5. Department of Health Sciences and Technology, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, Republic of Korea
3 figures and 2 additional files

Figures

Figure 1 with 3 supplements
Profile of CH in non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitor (ICI).

(A) Overall study design. The numbers indicate sample counts in each group. (B) Frequency of CH variant detection in each gene in NSCLC samples before (light blue) and after (blue) ICI treatment. (C)…

Figure 1—figure supplement 1
Variant calling and filtering scheme.

We collected numbers indicate count of variants after each variant filtering scheme (all samples/excluding controls).

Figure 1—figure supplement 2
Depth and annotation distributions from variants filtering scheme.

(A) Variant depth distributions from raw calls and putative clonal hematopoiesis of indeterminate potential (CHIP) variants. (B) Distribution of variant annotation from each variant filtering step.

Figure 1—figure supplement 3
Clonal hematopoiesis of indeterminate potential (CHIP) profiles from discovery cohort with panel sequencing (sample n = 100/91 for before treatment and after treatment).

(A) Gene distribution in before and after immune checkpoint inhibitor (ICI) treatment. Color indicates variant annotation. (B) Waterfall plot showing CHIP mutations from baseline, cohort samples.

Figure 2 with 3 supplements
Prevalence of CH in relation to various parameters.

(A–D) Discovery cohort (n = 100), (E–G) replication cohort (n = 180; see Methods for description). (A, E) CH prevalence by pathology (lung squamous cell carcinoma [LUSC] and lung adenocarcinoma …

Figure 2—figure supplement 1
Clonal hematopoiesis of indeterminate potential (CHIP) profiles, by stratified smoking status.

CHIP status was displayed using (A) binned variant allele frequency (VAF) and (B) variant count per patient. Colors indicate binned VAF and variants count.

Figure 2—figure supplement 2
Relationship between clonal hematopoiesis of indeterminate potential (CHIP) variant counts and clinical parameters.

CHIP variant counts and major clinical parameters were presented. Color indicates the binned number of CHIP variants.

Figure 2—figure supplement 3
Clonal hematopoiesis of indeterminate potential (CHIP) profiles from replicative cohort with peripheral blood mononuclear cell (PBMC) whole exome sequencing (WES) (n = 180).

(A) Variant depth distribution from raw and CHIP variant. Colored bar indicates variants cutoff, with depth = 40. (B) Distribution of variant annotation from each variant filtering step. (C) All …

Figure 3 with 9 supplements
Single-cell RNA sequencing (scRNA-seq) analysis detected myeloid-specific inflammatory signatures in patients with high CH burden.

(A) Uniform manifold approximation and projection (UMAP) plot of scRNA-seq data from the discovery cohort (n = 63). (B) Effect of pathology (left) and variant allele frequency (VAF) (right) on cell …

Figure 3—figure supplement 1
Single-cell RNA sequencing (scRNA-seq) profile of immune checkpoint inhibitor (ICI)-treated, non-small cell lung cancer (NSCLC) patients.

(A) UMAP plot of scRNA-seq data, with CH variant allele frequency (VAF) bins. (B) Cell-type-specific marker gene expression from each cluster. (C) Cell composition plot from each sample.

Figure 3—figure supplement 2
Gene expression of selected pathways for (A) IL-10 and (B) IL-1B.
Figure 3—figure supplement 3
Gene set enrichment analysis (GSEA) results from all annotated clusters.

Color represents normalized effect score (NES), and dot size represents adjusted p-values.

Figure 3—figure supplement 4
Gene set enrichment analysis (GSEA) results and representative gene expression patterns, associated with immune checkpoint inhibitor (ICI) response and clonal hematopoiesis of indeterminate potential (CHIP) variant allele frequency (VAF) bin.

(A) Results of GSEA analysis in response to ICI and CHIP VAF bins, from before treatment samples. Color represents normalized effect score (NES), and dot size represents adjusted p-values. (B) …

Figure 3—figure supplement 5
Single-cell RNA sequencing (scRNA-seq) weighted correlation network analysis (WGCNA) using hdWGCNA.

(A) WGCNA dendrogram, derived from myeloid gene expressions. (B) Cluster-wise ‘black’ module score distribution. (C) Gene ontology (GO) enrichment analysis of the black module genes. The colored bar …

Figure 3—figure supplement 6
SCENIC analysis for gene regulatory networks (GRNs) on single-cell RNA sequencing (scRNA-seq).

(A) Clustered, representative GRNs from scRNA-seq dataset. 1500 cells from each variant allele frequency (VAF) bin were presented for this visualization. Color represents GRN AUC scores. (B) …

Figure 3—figure supplement 7
Cell–cell interaction analysis using CellphoneDB.

Heatmap illustrating the numbers of cell–cell interactions using (A) high variant allele frequency (VAF) clonal hematopoiesis of indeterminate potential (CHIP) and (B) CHIP negative samples. (C) …

Figure 3—figure supplement 8
Survival plot from this cohort.

Survival curve using progression-free survival in clonal hematopoiesis of indeterminate potential (CHIP) negative (N = 71) and high-burden CHIP (N = 11), using survplot in R.

Figure 3—figure supplement 9
Bar plot of the top shared gene set enrichment analysis (GSEA) leading edge genes, using significantly enriched (adjusted p < 0.05 for each cluster).

Hypoxia and TNF-ɑ signaling pathways across clusters. The bars represent the count of clusters in which each gene is included in the leading edge.

Additional files

Supplementary file 1

Supplementary tables provided in an excel file.

(a) Clinical information of non-small cell lung cancer (NSCLC) cohort with immune checkpoint inhibitor (ICI) treatment. (b) Information of control samples. (c) List of clonal hematopoiesis of indeterminate potential (CHIP) variants detected from targeted sequencing. (d) List of CHIP variants detected from whole exome sequencing (WES). (e) Identified DEGs from annotated clusters of single-cell RNA sequencing (scRNA-seq). (f) Gene set enrichment analysis (GSEA) results related to myeloid lineage, related to Figure 3C. (g) Identified DEGs from each cluster by variant allele frequency (VAF) bin. (h) Gene-module annotation from weighted correlation network analysis (WGCNA).

https://cdn.elifesciences.org/articles/96951/elife-96951-supp1-v1.xlsx
MDAR checklist
https://cdn.elifesciences.org/articles/96951/elife-96951-mdarchecklist1-v1.docx

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