Detection of micro-metastases by flow cytometry in lymph nodes from patients with penile cancer

Development of a customizable mouse backbone spectral flow cytometry panel to delineate immune cell populations in normal and tumor tissues

Introduction

In vivo studies of cancer biology and assessment of therapeutic efficacy are critical to advancing cancer research and ultimately improving patient outcomes. Murine cancer models have proven to be an invaluable tool in pre-clinical studies. In this context, multi-parameter flow cytometry is a powerful method for elucidating the profile of immune cells within the tumor microenvironment and/or play a role in hematological diseases. However, designing an appropriate multi-parameter panel to comprehensively profile the increasing diversity of immune cells across different murine tissues can be extremely challenging.

Methods

To address this issue, we designed a panel with 13 fixed markers that define the major immune populations -referred to as the backbone panel- that can be profiled in different tissues but with the option to incorporate up to seven additional fluorochromes, including any marker specific to the study in question.

Results

This backbone panel maintains its resolution across different spectral flow cytometers and organs, both hematopoietic and non-hematopoietic, as well as tumors with complex immune microenvironments.

Discussion

Having a robust backbone that can be easily customized with pre-validated drop-in fluorochromes saves time and resources and brings consistency and standardization, making it a versatile solution for immuno-oncology researchers. In addition, the approach presented here can serve as a guide to develop similar types of customizable backbone panels for different research questions requiring high-parameter flow cytometry panels.

Precisional detection of lymph node metastasis using tFCM in colorectal cancer

The detection of colorectal cancer (CRC) lymph node (LN) metastases significantly influences treatment choices, yet identifying them in samples is time-consuming and error-prone. To enhance efficiency, we have established a LN metastasis detection method utilizing triple-parameter flow cytometry (tFCM) and have conducted a comparative assessment of its accuracy and cost-effectiveness in contrast to conventional pathological examinations. This technique utilized biomarkers cytokeratin 20 (CK20), epithelial cell adhesion molecules (EpCAM), and Pan-CK. tFCM's sensitivity was validated by analyzing known cell line concentrations (SW480 and SW620) in peripheral blood mononuclear cells (PBMCs), with CK20, EpCAM, and Pan-CK showing significant expression in CRC cell lines but not in PBMCs. A strong linear correlation was observed in the mixed leukocyte environment (R 2 = 0.9988). Subsequently, tFCM and pathological sections were employed to analyze LNs from CRC patients, enabling comparison of detection accuracy. Within the 36 LNs studied, tFCM successfully identified tumor cells with varying metastasis degrees, including micro-metastasis and isolated tumor cell clusters. Notably, relying solely on pathological sections led to a potential 25% misdiagnosis rate for LNs. In contrast, tFCM effectively minimized this risk. In summary, compared to traditional pathological sections, tFCM is a more advantageous method for detecting nodal metastasis in CRC patients, offering a more precise prognosis for these patients.