Document Type

Article

Publication Date

5-13-2024

Comments

This article is the author's final published version in Cancer Cell, Volume 42, Issue 5, May 2024, Pages 759 - 779.e12.

The published version is available at https://doi.org/10.1016/j.ccell.2024.04.008.

Copyright © 2024 The Authors

Abstract

The lack of comprehensive diagnostics and consensus analytical models for evaluating the status of a patient's immune system has hindered a wider adoption of immunoprofiling for treatment monitoring and response prediction in cancer patients. To address this unmet need, we developed an immunoprofiling platform that uses multiparameter flow cytometry to characterize immune cell heterogeneity in the peripheral blood of healthy donors and patients with advanced cancers. Using unsupervised clustering, we identified five immunotypes with unique distributions of different cell types and gene expression profiles. An independent analysis of 17,800 open-source transcriptomes with the same approach corroborated these findings. Continuous immunotype-based signature scores were developed to correlate systemic immunity with patient responses to different cancer treatments, including immunotherapy, prognostically and predictively. Our approach and findings illustrate the potential utility of a simple blood test as a flexible tool for stratifying cancer patients into therapy response groups based on systemic immunoprofiling.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional Files
Document S1.pdf (9140 kB)
Figures S1–S8
Table S1.xlsx (19 kB)
List of antibodies used for staining of the main panel, related to cell staining for flow cytometry, related to Figure 1 and STAR Methods
Table S2.xlsx (226 kB)
List of populations used for cytometry analysis and corresponding markers, related to Figure 1 and STAR Methods
Table S3.xlsx (353 kB)
Machine Learning models parameters and quality metrics, related to Figure 1 and STAR Methods
Table S4.xlsx (74 kB)
Demographic and other characteristics of the main cohort, related to Figures 2 and 3 and STAR Methods
Table S5.xlsx (14 kB)
Differentially distributed populations for healthy vs. cancer classifier, related to Figure 2 and STAR Methods
Table S6.xlsx (342 kB)
Cluster populations and characterization, related to Figures 3 and 4 and STAR Methods
Table S7.xlsx (217 kB)
RNA-seq open-source datasets, related to Figure 5 and STAR Methods
Table S8.xlsx (410 kB)
Immunotype Signature Score coefficients for different cohorts, related to Figures 5, 6, and 7 and STAR Methods
Table S9.xlsx (144 kB)
Demographic and other characteristics of two HNSCC cohorts, related to Figure 7 and STAR Methods
Document S2.pdf (20465 kB)

PubMed ID

38744245

Language

English

Download

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.