Decoupled neoantigen cross-presentation by dendritic cells limits anti-tumor immunity against tumors with heterogeneous neoantigen expression

Abstract

Cancer immunotherapies, in particular checkpoint blockade immunotherapy (CBT), can induce control of cancer growth, with a fraction of patients experiencing durable responses. However, the majority of patients currently do not respond to CBT and the molecular determinants of resistance have not been fully elucidated. Mounting clinical evidence suggests that the clonal status of neoantigens (NeoAg) impacts the anti-tumor T cell response. High intratumor heterogeneity (ITH), where the majority of NeoAgs are expressed subclonally, is correlated with poor clinical response to CBT and poor infiltration with tumor-reactive T cells. However, the mechanism by which ITH blunts tumor-reactive T cells is unclear. We developed a transplantable murine lung cancer model to characterize the immune response against a defined set of NeoAgs expressed either clonally or subclonally to model low or high ITH, respectively. Here we show that clonal expression of a weakly immunogenic NeoAg with a relatively strong NeoAg increased the immunogenicity of tumors with low but not high ITH. Mechanistically we determined that clonal NeoAg expression allowed cross-presenting dendritic cells to acquire and present both NeoAgs. Dual NeoAg presentation by dendritic cells was associated with a more mature DC phenotype and a higher stimulatory capacity. These data suggest that clonal NeoAg expression can induce more potent anti-tumor responses due to more stimulatory dendritic cell : T cell interactions. Therapeutic vaccination targeting subclonally expressed NeoAgs could be used to boost anti-tumor T cell responses.

Data availability

All raw data are uploaded as source data files.

Article and author information

Author details

  1. Kim Bich Nguyen

    Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2269-6809
  2. Malte Roerden

    Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    No competing interests declared.
  3. Christopher J Copeland

    Department of Biology, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6882-3359
  4. Coralie M Backlund

    Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    No competing interests declared.
  5. Nory G Klop-Packel

    Department of Biology, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    No competing interests declared.
  6. Tanaka Remba

    Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    No competing interests declared.
  7. Byungji Kim

    Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8131-5255
  8. Nishant K Singh

    Department of Biology, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    No competing interests declared.
  9. Michael E Birnbaum

    Department of Biology, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    Michael E Birnbaum, is an equity holder in 3T Biosciences, and is a co-founder, equity holder, and consultant of Kelonia Therapeutics and Abata Therapeutics..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2281-3518
  10. Darrell J Irvine

    Department of Biology, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    No competing interests declared.
  11. Stefani Spranger

    Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, United States
    For correspondence
    spranger@mit.edu
    Competing interests
    Stefani Spranger, is a SAB member for Related Sciences,Arcus Biosciences, Ankyra Therapeutics and Venn Therapeutics. S.S. is a co-founder ofDanger Bio. S.S. is a consultant for TAKEDA, Merck, Tango Therapeutics, Dragonfly andRibon Therapeutics and receives funding for unrelated projects from Leap Therapeutics..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3257-4546

Funding

Melanoma Research Alliance

  • Stefani Spranger

Lung Cancer Research Foundation

  • Stefani Spranger

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: All experimental animal procedures were approved by the Committee on Animal Care (CAC/IACUC) at MIT.

Copyright

© 2023, Nguyen et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,779
    views
  • 256
    downloads
  • 5
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Kim Bich Nguyen
  2. Malte Roerden
  3. Christopher J Copeland
  4. Coralie M Backlund
  5. Nory G Klop-Packel
  6. Tanaka Remba
  7. Byungji Kim
  8. Nishant K Singh
  9. Michael E Birnbaum
  10. Darrell J Irvine
  11. Stefani Spranger
(2023)
Decoupled neoantigen cross-presentation by dendritic cells limits anti-tumor immunity against tumors with heterogeneous neoantigen expression
eLife 12:e85263.
https://doi.org/10.7554/eLife.85263

Share this article

https://doi.org/10.7554/eLife.85263

Further reading

    1. Cancer Biology
    2. Evolutionary Biology
    Susanne Tilk, Judith Frydman ... Dmitri A Petrov
    Research Article

    In asexual populations that don’t undergo recombination, such as cancer, deleterious mutations are expected to accrue readily due to genome-wide linkage between mutations. Despite this mutational load of often thousands of deleterious mutations, many tumors thrive. How tumors survive the damaging consequences of this mutational load is not well understood. Here, we investigate the functional consequences of mutational load in 10,295 human tumors by quantifying their phenotypic response through changes in gene expression. Using a generalized linear mixed model (GLMM), we find that high mutational load tumors up-regulate proteostasis machinery related to the mitigation and prevention of protein misfolding. We replicate these expression responses in cancer cell lines and show that the viability in high mutational load cancer cells is strongly dependent on complexes that degrade and refold proteins. This indicates that the upregulation of proteostasis machinery is causally important for high mutational burden tumors and uncovers new therapeutic vulnerabilities.

    1. Cancer Biology
    2. Cell Biology
    Kourosh Hayatigolkhatmi, Chiara Soriani ... Simona Rodighiero
    Tools and Resources

    Understanding the cell cycle at the single-cell level is crucial for cellular biology and cancer research. While current methods using fluorescent markers have improved the study of adherent cells, non-adherent cells remain challenging. In this study, we addressed this gap by combining a specialized surface to enhance cell attachment, the FUCCI(CA)2 sensor, an automated image analysis pipeline, and a custom machine learning algorithm. This approach enabled precise measurement of cell cycle phase durations in non-adherent cells. This method was validated in acute myeloid leukemia cell lines NB4 and Kasumi-1, which have unique cell cycle characteristics, and we tested the impact of cell cycle-modulating drugs on NB4 cells. Our cell cycle analysis system, which is also compatible with adherent cells, is fully automated and freely available, providing detailed insights from hundreds of cells under various conditions. This report presents a valuable tool for advancing cancer research and drug development by enabling comprehensive, automated cell cycle analysis in both adherent and non-adherent cells.