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

Immunotherapy Clinical Trial

Official title:

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

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04807127
• Other study ID #: S63357
• Status: Recruiting
• Start date: February 1, 2020
• Est. completion date: January 31, 2024

Study information

• Verified date: March 2023
• Source: Universitaire Ziekenhuizen KU Leuven
• Contact: Els Wauters, MD, PhD
• Phone: +3216340942
• Email: els.wauters[@]uzleuven.be
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

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.

Description:

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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 60
• Est. completion date: January 31, 2024
• Est. primary completion date: January 31, 2024
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 120 Years

Eligibility

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.

Related Conditions & MeSH terms

• Immune-related Adverse Events
• Immunotherapy
• Lung Diseases, Interstitial
• Pneumonia
• Pneumonitis, Interstitial

Intervention

Drug:
• Immune checkpoint blockade
ICI, administered as standard-of-care treatment
• Targeted therapy
TKI, administered as standard-of-care treatment

Radiation:
• Radiotherapy
RT, administered as standard-of-care treatment

Locations

Country	Name	City	State
Belgium	Universitaire Ziekenhuizen Leuven	Leuven	Flemish Brabant

Sponsors (2)

Lead Sponsor	Collaborator
Universitaire Ziekenhuizen KU Leuven	KU Leuven

Country where clinical trial is conducted

Belgium, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	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
Primary	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	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
Secondary	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