Heterogeneity of Dendritic Cells in Colon and Non-small Cell Lung Cancer (TUM-DC)

Heterogeneity of Dendritic Cells and Other Cells of Myeloid and Lymphoid Origin in Colon and Non-small Cell Lung Cancer

Prospective study with the use of biological samples. The centers involved are the Thoracic Surgery and Surgery 1 Units of the San Gerardo Hospital in Monza.

Study Overview

• Status: Recruiting
• Conditions: Non-small Cell Lung Cancer
• Intervention / Treatment: Biological: Bioinformatics analysis of single cell transcriptomics data

Detailed Description

BACKGROUND The activation of adaptive immune responses depends on dendritic cells (DCs) and macrophages, myeloid cells of the innate immune system specialized in antigen presentation and in the activation of T cells. This peculiarity of myeloid cells is fundamental not only during diseases infectious but also in the context of cancer, as phagocytes pick up antigens associated with cancer cells and present them to T cells within the tumor microenvironment or in tumor-draining lymph nodes to obtain antitumor responses.

In particular, a positive correlation was observed between the overall tumor content of DC and the survival of cancer patients with different tumors, as well as a better reactivity to therapies based on the use of immunocheckpoint inhibitors (ICB).

The presence of different dendritic cell subtypes has recently been revealed, as well as a specific adaptation of each subtype to the tumor environment.

This is a critical point since the functional heterogeneity of DCs, macrophages and T cells in the tumor microenvironment is probably one of the factors responsible for the success or failure of anticancer immunotherapies. ICB-based therapies have revolutionized the treatment of patients with cancers, such as melanoma and lung cancer, but are currently only beneficial to a minority of patients. Improving understanding of the tumor immune microenvironment is the key to predicting clinical responses to existing therapies and possibly the development of new immunotherapies.

RATIONALE Myeloid cells, such as dendritic cells and macrophages infiltrate many different types of tumors and can exert an antitumor function by activating T and NK cells, or they can carry out a pro-tumor activity by producing anti-inflammatory cytokines and inhibitory molecules. The presence within the tumor of several conventional DC subtypes has been associated with a better prognosis while a pro-tumor function has been proposed for unconventional DCs such as CD14 + CD1c + DC. The presence of macrophages has been associated with a protumoral action.

The investigators hypothesize that the functional heterogeneity of myeloid cells and T cells within the tumor microenvironment is one of the factors responsible for the success or failure of antitumor immune responses. High resolution definition of myeloid cell subtypes and tumor associated T cells, their phenotype, distribution within the tumor, as well as their functional characteristics will help to understand the complexity of the tumor microenvironment.

STUDY DESIGN Upon collection, each sample will be identified and labeled with a unique ID. The pathologist will sample the material and select the tissue that can be used for the experiment after having taken all that is needed for diagnostic purposes. The research sample will be placed in test tubes and kept on ice. It will then be sent to University of Milano-Bicocca laboratory. The tumor will be cut into pieces and single cell suspensions will be prepared with the human tumor dissociation kit and the gentleMACS ™ dissociator (Miltenyi Biotech) according to the standard protocol. Cell suspensions will then be isolated by density gradient centrifugation.

The investigators will analyze approximately 60 patients for immunofluorescence studies and 4 patients for single cell transcriptomic analyzes (single cell RNA-seq). Single cell analysis performed by 4 patients has already shown to be sufficient to identify different subtypes of immune cells. Immune cells will be treated to obtain a cell suspension enriched in myeloid cells. This will allow for accurate subtypes analysis of DC, macrophages and CD4 + T cells and to identify even very rare populations that could be lost in unselected samples due to dilution. The pre-sorting strategy will be based on the expression of CD45 and MHC class II and on the absence of expression of CD3, CD19, CD56, Ly6G to exclude T, B, NK and neutrophils.

Residual material will not be stored. It is assumed that patients will be enrolled and analyzed over a 5-year period.

There are 5 diifferent tasks:

Task1: Preparation and sequencing of the single cell RNA-seq library; Task 2: Single cell RNA-seq bioinformatics analysis; Task 3: Flow cytometric analysis of the DC subtypes present in the tumor microenvironment; Task 4: Spatial distributions of DC subtypes in the tumor microenvironment Task 5: Evaluation of the association between subtypes of myeloid cells present in the tumor microenvironment and survival;

The study will end with the bioinformatics analysis of the data and the validation of them through flow cytometric analyzes

• Study Type: Observational
• Enrollment (Estimated): 64

Contacts and Locations

• Study Contact: Name: Francesca Granucci; Phone Number: 0264483553; Email: francesca.granucci@unimib.it
• Study Contact Backup: Name: Marco Scarci; Phone Number: 3459364819; Email: m.scarci@asst-monza.it

Study Locations

• Italy
  • Monza, Italy
    • Not yet recruiting
    • ASST Monza-C. CHIRURGIA GENERALE E D'URGENZA I
    • Contact: Luca Nespoli
  • Monza, Italy
    • Recruiting
    • ASST Monza-Ospedale San Gerardo, S.C. Chirurgia Toracica
    • Contact: Francesca Granucci
    • Contact: Marco Scarci

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Patients with NSCLC (primary tumor, adjacent healthy tissue, blood) or colon cancer (primary tumor, normal adjacent tissue, blood)

Description

Inclusion Criteria:

• men and women aged ≥18 years;
• clinical diagnosis confirmed by common investigations to establish the presence of colon or lung cancer;
• lesions> 1 cm;
• legal capacity to give informed consent in accordance with ICH / EU GCP and national / local regulations.

Exclusion Criteria:

• pregnancy;
• presumed pregnancy;
• known coagulation defects;
• alcohol or drug abuse

Study Plan

How is the study designed?

Design Details

• Observational Models: Cohort
• Time Perspectives: Prospective

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Intervention / Treatment

Patients with NSCLC or with colon cancer; The subjects are men or women with aged more than 18 years suffering from colon or lung cancer; The lesions are more than 1 cm. They are also able to give informed consent. The pathologist will sample the material and select the tissue that can be used for the experiment after having taken all that is needed for diagnostic purposes. The research sample will be placed in test tubes and kept on ice. It will then be sent to University of Milano-Bicocca laboratory whrere It will analyze approximately 60 patients for immunofluorescence studies and 4 patients for single cell transcriptomic analyzes

Biological: Bioinformatics analysis of single cell transcriptomics data; Sample collection: Myeloid cell purification + Single cell sequencing; Primary analysis: QC sequencing data + Reads alignment + UMI quantification; Bioinformatics analysis: Quality Control (Number of genes, UMI content,%mitochondrial genes, % riboprotein genes,Filtering low quality cells) + Normalization and scaling (Normalization, Remove unwanted sources of variation, HVG detection) + PCA Clustering Markers (PCA and PC selection, Clustering, t-SNE, Differential expression for markers identification); Validation: FACS analysis + immunohistochemistry

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Single cell bioinformatics analysis RNA-seq	For the analysis of single-cell RNA-seq data we will exploit the most recent methodologies provided by both 10x Genomics and custom R / Python scripts to perform the identification and characterization of cell subsets.	Until the end of the study (approximately 5 years).
Single cell RNA-seq library preparation and sequencing.	10,000 cells for each sample will be loaded on an instrument called Chromium 10X (10x genomics).	Until the end of the study (approximately 5 years).

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Spatial distributions of DC subtypes in the tumor microenvironment	The Shapiro-Wilks test will be used to check whether continuous variables follow a normal distribution. Comparisons between groups will be performed using t-tests or analysis of variance (ANOVA) when more than two groups are compared. In case of rejection of the null hypothesis for the ANOVA tests, pairwise comparisons will be made using the Tukey method for checking the α error in the presence of multiple non-orthogonal comparisons. If the variables are not normally distributed, the corresponding non-parametric tests (Wilcoxon Mann Whitney and Kruskal-Wallis test) will be applied. Given the large number of tests performed, the positive false discovery rate (pFDR) method will be applied to take into account the multiplicity problem.	Until the end of the study (approximately 5 years).
Correlation between subtypes of myeloid cells present in the tumor microenvironment and survival	A multivariate Cox model for overall survival and one for disease-free survival, including in each model all genes jointly using the "minimum absolute shrinkage and selection operator" (LASSO) method to select the actual genes associated with survival and estimate the hazard ratio (HR) and the corresponding 95% CI.	Until the end of the study (approximately 5 years).

Collaborators and Investigators

• Sponsor: University of Milano Bicocca

Publications and helpful links

General Publications

• Gornati L, Zanoni I, Granucci F. Dendritic Cells in the Cross Hair for the Generation of Tailored Vaccines. Front Immunol. 2018 Jun 27;9:1484. doi: 10.3389/fimmu.2018.01484. eCollection 2018.
• Bottcher JP, Reis e Sousa C. The Role of Type 1 Conventional Dendritic Cells in Cancer Immunity. Trends Cancer. 2018 Nov;4(11):784-792. doi: 10.1016/j.trecan.2018.09.001. Epub 2018 Sep 29.
• Hildner K, Edelson BT, Purtha WE, Diamond M, Matsushita H, Kohyama M, Calderon B, Schraml BU, Unanue ER, Diamond MS, Schreiber RD, Murphy TL, Murphy KM. Batf3 deficiency reveals a critical role for CD8alpha+ dendritic cells in cytotoxic T cell immunity. Science. 2008 Nov 14;322(5904):1097-100. doi: 10.1126/science.1164206.
• Eisenbarth SC. Dendritic cell subsets in T cell programming: location dictates function. Nat Rev Immunol. 2019 Feb;19(2):89-103. doi: 10.1038/s41577-018-0088-1.
• Mingozzi F, Spreafico R, Gorletta T, Cigni C, Di Gioia M, Caccia M, Sironi L, Collini M, Soncini M, Rusconi M, von Andrian UH, Chirico G, Zanoni I, Granucci F. Prolonged contact with dendritic cells turns lymph node-resident NK cells into anti-tumor effectors. EMBO Mol Med. 2016 Sep 1;8(9):1039-51. doi: 10.15252/emmm.201506164. Print 2016 Sep.

Study record dates

Study Major Dates

• Study Start (Actual): February 9, 2021
• Primary Completion (Estimated): February 9, 2026
• Study Completion (Estimated): February 9, 2026

Study Registration Dates

• First Submitted: February 17, 2021
• First Submitted That Met QC Criteria: March 4, 2021
• First Posted (Actual): March 9, 2021

Study Record Updates

• Last Update Posted (Estimated): January 1, 2024
• Last Update Submitted That Met QC Criteria: December 29, 2023
• Last Verified: December 1, 2023

More Information

Terms related to this study

• Keywords: lung; cancer; colon cancer; dendritic cells
• Additional Relevant MeSH Terms: Respiratory Tract Diseases; Neoplasms; Lung Diseases; Neoplasms by Site; Respiratory Tract Neoplasms; Thoracic Neoplasms; Carcinoma, Bronchogenic; Bronchial Neoplasms; Lung Neoplasms; Carcinoma, Non-Small-Cell Lung
• Other Study ID Numbers: TUM-DC

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No