A Single-cell Approach to Identify Biomarkers of Pulmonary Toxicity for Immune Checkpoint Blockade

Study Overview
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Brief Summary
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The main goal of this prospective non-interventional exploratory monocentric study is to characterize the immune cell composition of bronchoalveolar lavage (BAL) fluid from cancer patients experiencing cancer therapy-induced pneumonitis on a single-cell scale. These mechanistic insights can directly lead to putative diagnostic biomarkers and therapeutic targets. A second highly clinically relevant hypothesis is that single-cell profiling of blood samples will reveal circulating biomarkers of ICB toxicity, making non-invasive diagnosis feasible.

Detailed Description
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The investigators will apply single cell RNA- and TCR-sequencing on up to 5,000 single cells per sample. Additionally, cell surface protein expression can be integrated with the transcriptional information. Various bioinformatics pipelines, including Seurat, will be used to identify different cell clusters, which through marker gene expression will be assigned to known cell types, cellular subtypes or phenotypes. For instance, this will make it possible to monitor the abundance of PD-1/PD-L1 expressing T-cells, cytotoxic T-cells, immune-suppressive myeloid cells etc. The following parameters at single-cell level will be relevant, amongst others: The composition and relative abundancies of established immune cell types (e.g. T cells (CD4+, CD8+ and regulatory subsets), NK cells, B cells, MDSCs, macrophages, neutrophils, dendritic cells). Transcriptomic data for each of these immune cell subtypes will be analyzed, allowing characterization of specific gene expression programs that define specific phenotypic states. Composition of all stromal cellular subtypes identified by single-cell transcriptomics. A gene regulatory network for each cell type and cellular subtype (or cell state) will be established and master transcriptional regulators will be identified. Individual T-cells and T-cell subclusters will be classified based on interferon activation, high rates of proliferation and transcription and increased granzyme expression, which are all indicative of T-cell activation. Blood samples will be subjected to similar single-cell experimental procedures. First, peripheral blood mononuclear cells (PBMC) are isolated using Ficoll density gradient centrifugation. Single-cell transcriptome analysis in combination with CITE-seq will be performed on 5000 PBMC. Cellular composition will be determined using the same bioinformatic pipelines as used for processing the BAL fluid cells.

Official Title
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A Single-cell Approach to Identify Biomarkers of Pulmonary Toxicity for Immune Checkpoint Blockade

Conditions
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Pneumonitis, Interstitial, Immunotherapy, Immune-related Adverse Events

Intervention / Treatment
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* Drug: Immune checkpoint blockade
* Drug: Targeted therapy
* Radiation: Radiotherapy


Participation Criteria
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Eligibility Criteria
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Inclusion criteria: Adult M/F/X (>= 18 years) Patients receiving or having received treatment per guidelines Patients undergoing bronchoscopy with BAL, for possible cancer treatment-induced pneumonitis Not included in other clinical trials Signed informed consent form Exclusion criteria: • Collected material not suitable for further processing in this study (e.g. bad quality). This decision will be made in consultation with a lab technician and/or bio-informatician, specialized in single-cell analysis.

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 120 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| ICI-pneumonitis<br>Cancer patients experiencing ICI-pneumonitis | Drug: Immune checkpoint blockade<br>* ICI, administered as standard-of-care treatment<br>* Other names: Durvalumab;|
| Radiotherapy induced pneumonitis<br>Cancer patients experiencing RT-pneumonitis | Radiation: Radiotherapy<br>* RT, administered as standard-of-care treatment<br>|
| TKI-induced pneumonitis<br>Cancer patients experiencing TKI-induced pneumonitis | Drug: Targeted therapy<br>* TKI, administered as standard-of-care treatment<br>* Other names: TKI;|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Immune cell proportions, as determined by scRNA-seq, present in ICI-/RT-/TKI-induced pneumonitis BAL fluid | By identifying and statistically comparing the percentages of immune cell subtypes present in ICI-/RT-/TKI-induced pneumonitis BAL fluid, we aim to i) understand which immune processes drive these adverse events ii) identify putative molecular biomarkers iii) identify putative therapeutic targets | From date of inclusion until study completion, on average 2 years | 
| Differentially expressed genes in BAL fluid, as determined by scRNA-seq, discriminating ICI-/RT-/TKI-induced pneumonitis | By identifying differentially expressed genes in ICI- vs. RT- vs. TKI-induced pneumonitis BAL fluid, we aim to i) understand which immune processes drive these adverse events ii) identify putative molecular biomarkers iii) identify putative therapeutic targets | From date of inclusion until study completion, on average 2 years | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Immune cell proportions, as determined by scRNA-seq, present in ICI-/RT-/TKI-induced pneumonitis peripheral blood mononuclear cells | By identifying and statistically comparing the percentages of immune cell subtypes present in ICI-/RT-/TKI-induced pneumonitis peripheral blood mononuclear cells, we aim to i) understand which immune processes drive these adverse events ii) identify putative molecular biomarkers iii) identify putative therapeutic targets | From date of inclusion until study completion, on average 2 years | 
| Differentially expressed genes in PBMC, as determined by scRNA-seq, discriminating ICI-/RT-/TKI-induced pneumonitis | By identifying differentially expressed genes in ICI- vs. RT- vs. TKI-induced pneumonitis PBMC, we aim to i) understand which immune processes drive these adverse events ii) identify putative molecular biomarkers iii) identify putative therapeutic targets | From date of inclusion until study completion, on average 2 years |