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Predictive Immune Modeling of Solid Tumors
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Predictive Immune Modeling of Solid Tumors

Published on: February 25, 2020

Integrating genomic signatures for immunologic discovery.

W Nicholas Haining1, E John Wherry

  • 1Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA.

Immunity
|March 2, 2010
PubMed
Summary
This summary is machine-generated.

Understanding immune cell differences is key for vaccine and pathogen research. Gene expression signatures offer a powerful way to analyze these complex adaptive immune responses.

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Mapping Infant Immunity with Minimal Input: Integrative Single-Cell and Multiomic Profiling
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Mapping Infant Immunity with Minimal Input: Integrative Single-Cell and Multiomic Profiling

Published on: April 3, 2026

Area of Science:

  • Immunology
  • Genomics
  • Systems Biology

Background:

  • Adaptive immune responses exhibit heterogeneity crucial for understanding cell differentiation and immunity.
  • Flow cytometry has been the traditional method for analyzing immune cell populations.
  • Genome-scale technologies offer new ways to define cellular properties through gene expression.

Purpose of the Study:

  • To explore the utility of gene expression signatures in dissecting adaptive immune response complexity.
  • To integrate phenotypic and genomic data for a comprehensive understanding of immune cell states.
  • To investigate how gene expression signatures can serve as surrogates for cell phenotypes and functions.

Main Methods:

  • Utilizing genome-scale technologies to define gene expression signatures.
  • Analyzing expression signatures across diverse experimental conditions.
  • Integrating expression signature data with functional analysis of component genes.

Main Results:

  • Genomic signatures can represent discrete biological properties of cell populations.
  • Expression signatures can serve as surrogates for phenotypes, functions, and cell states.
  • Integration of signatures allows for cross-experiment and cross-species comparisons.

Conclusions:

  • Well-defined expression signatures can enhance the dissection of adaptive immune responses.
  • Integrating genomic data with functional analysis provides new opportunities to map immune responses.
  • This approach can advance the study of immune memory and protective immunity against vaccines and pathogens.