Dataset Information

Protocol for simultaneous analysis of peripheral and intratumoral lymphocyte function by flow cytometry.

ABSTRACT: Here, we present a protocol for the simultaneous analysis of peripheral and intratumoral lymphocyte function by flow cytometry. Using tumor and blood samples from patients with colorectal cancer, we describe steps for tumor digestion, pre-labeling of the tumor-infiltrating leukocytes (TILs), and activation and labeling of the total cells (TILs and whole blood cells). For complete details on the use and execution of this protocol, please refer to Thibaudin et al.¹.

SUBMITTER: Daumoine S

PROVIDER: S-EPMC10630783 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Protocol for simultaneous analysis of peripheral and intratumoral lymphocyte function by flow cytometry.

Daumoine Susy S Hampe Léa L Limagne Emeric E Ghiringhelli François F Thibaudin Marion M

STAR protocols 20231031 4

Here, we present a protocol for the simultaneous analysis of peripheral and intratumoral lymphocyte function by flow cytometry. Using tumor and blood samples from patients with colorectal cancer, we describe steps for tumor digestion, pre-labeling of the tumor-infiltrating leukocytes (TILs), and activation and labeling of the total cells (TILs and whole blood cells). For complete details on the use and execution of this protocol, please refer to Thibaudin et al.<sup>1</sup>. ...[more]

PMID: 37910510

Similar Datasets

Project description:BackgroundImmune dysregulation is a hallmark of autoimmune diseases of the central nervous system (CNS), characterized by an excessive immune response, and primary CNS tumors (pCNS-tumors) showing a highly immunosuppressive parenchymal microenvironment.MethodsAiming to provide novel insights into the pathogenesis of CNS autoimmunity and cerebral tumor immunity, we analyzed the peripheral blood (PB) and cerebrospinal fluid (CSF) of 81 autoimmune limbic encephalitis (ALE), 148 relapsing-remitting multiple sclerosis (RRMS), 33 IDH-wildtype glioma, 9 primary diffuse large B cell lymphoma of the CNS (CNS-DLBCL), and 110 controls by flow cytometry (FC). Additionally, an in-depth immunophenotyping of the PB from an independent cohort of 20 RRMS and 18 IDH-wildtype glioblastoma patients compared to 19 controls was performed by FC combined with unsupervised computational approaches.ResultsWe identified alterations in peripheral and intrathecal adaptive immunity, mainly affecting the T cell (Tc) but also the B cell (Bc) compartment in ALE, RRMS, and pCNS-tumors compared to controls. ALE, RRMS, and pCNS-tumors featured higher expression of the T cell activation marker HLA-DR, which was even more pronounced in pCNS-tumors than in ALE or RRMS. Glioblastoma patients showed signs of T cell exhaustion that were not visible in RRMS patients. In-depth characterization of the PB revealed differences mainly in the T effector and memory compartment between RRMS and glioblastoma patients and similar alterations in the Bc compartment, including atypical Bc, CD19+CD20- double negative Bc, and plasma cells. PB and CSF mFC together with CSF routine parameters could reliably differentiate ALE and RRMS from pCNS-tumors facilitating early diagnosis and treatment.ConclusionsALE, RRMS, and pCNS-tumors show distinct but partially overlapping changes mainly in HLA-DR+ Tc, memory Tc, exhausted Tc, and Bc subsets providing insights into disease pathogenesis. Moreover, mFC shows diagnostic potential facilitating early diagnosis and treatment.

Project description:Adaptive immune responses are complex dynamic processes whereby B and T cells undergo division and differentiation triggered by pathogenic stimuli. Deregulation of the response can lead to severe consequences for the host organism ranging from immune deficiencies to autoimmunity. Tracking cell division and differentiation by flow cytometry using fluorescent probes is a major method for measuring progression of lymphocyte responses, both in vitro and in vivo. In turn, mathematical modeling of cell numbers derived from such measurements has led to significant biological discoveries, and plays an increasingly important role in lymphocyte research. Fitting an appropriate parameterized model to such data is the goal of these studies but significant challenges are presented by the variability in measurements. This variation results from the sum of experimental noise and intrinsic probabilistic differences in cells and is difficult to characterize analytically. Current model fitting methods adopt different simplifying assumptions to describe the distribution of such measurements and these assumptions have not been tested directly. To help inform the choice and application of appropriate methods of model fitting to such data we studied the errors associated with flow cytometry measurements from a wide variety of experiments. We found that the mean and variance of the noise were related by a power law with an exponent between 1.3 and 1.8 for different datasets. This violated the assumptions inherent to commonly used least squares, linear variance scaling and log-transformation based methods. As a result of these findings we propose a new measurement model that we justify both theoretically, from the maximum entropy standpoint, and empirically using collected data. Our evaluation suggests that the new model can be reliably used for model fitting across a variety of conditions. Our work provides a foundation for modeling measurements in flow cytometry experiments thus facilitating progress in quantitative studies of lymphocyte responses.

Project description:Flow cytometry is a powerful method, which is widely used for high-throughput quantitative and qualitative analysis of cells. However, its straightforward applicability for extracellular vesicles (EVs) and mainly exosomes is hampered by several challenges, reflecting mostly the small size of these vesicles (exosomes: ~80-200 nm, microvesicles: ~200-1,000 nm), their polydispersity, and low refractive index. The current best and most widely used protocol for beads-free flow cytometry of exosomes uses ultracentrifugation (UC) coupled with floatation in sucrose gradient for their isolation, labeling with lipophilic dye PKH67 and antibodies, and an optimized version of commercial high-end cytometer for analysis. However, this approach requires an experienced flow cytometer operator capable of manual hardware adjustments and calibration of the cytometer. Here, we provide a novel and fast approach for quantification and characterization of both exosomes and microvesicles isolated from cell culture media as well as from more complex human samples (ascites of ovarian cancer patients) suitable for multiuser labs by using a flow cytometer especially designed for small particles, which can be used without adjustments prior to data acquisition. EVs can be fluorescently labeled with protein-(Carboxyfluoresceinsuccinimidyl ester, CFSE) and/or lipid- (FM) specific dyes, without the necessity of removing the unbound fluorescent dye by UC, which further facilitates and speeds up the characterization of microvesicles and exosomes using flow cytometry. In addition, double labeling with protein- and lipid-specific dyes enables separation of EVs from common contaminants of EV preparations, such as protein aggregates or micelles formed by unbound lipophilic styryl dyes, thus not leading to overestimation of EV numbers. Moreover, our protocol is compatible with antibody labeling using fluorescently conjugated primary antibodies. The presented methodology opens the possibility for routine quantification and characterization of EVs from various sources. Finally, it has the potential to bring a desired level of control into routine experiments and non-specialized labs, thanks to its simple bead-based standardization.

Dataset Information

Protocol for simultaneous analysis of peripheral and intratumoral lymphocyte function by flow cytometry.

Publications

Protocol for simultaneous analysis of peripheral and intratumoral lymphocyte function by flow cytometry.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets