Leiden University Scholarly Publications

Lapuente-Santana, O.; Sturm, G.; Kant, J.; Ausserhofer, M.; Zackl, C.; Zopoglou, M.; ... ; Finotello, F. (2024)

Multimodal analysis unveils tumor microenvironment heterogeneity linked to immune and evasion

Article / Letter to editor

The cellular and molecular heterogeneity of tumors is a major obstacle to cancer immunotherapy. Here, we use a systems biology approach to derive a signature of the main sources of heterogeneity in the tumor microenvironment (TME) from lung cancer transcriptomics. We demonstrate that this signature, which we called iHet, is conserved in different cancers and associated with antitumor immunity. Through analysis of single-cell and spatial transcriptomics data, we trace back the cellular origin of the variability explaining the iHet signature. Finally, we demonstrate that iHet has predictive value for cancer immunotherapy, which can be further improved by disentangling three major determinants of anticancer immune responses: activity of immune cells, immune infiltration or exclusion, and cancer-cell foreignness. This work shows how transcriptomics data can be integrated to derive a holistic representation of the phenotypic heterogeneity of the TME and to predict its...Show more The cellular and molecular heterogeneity of tumors is a major obstacle to cancer immunotherapy. Here, we use a systems biology approach to derive a signature of the main sources of heterogeneity in the tumor microenvironment (TME) from lung cancer transcriptomics. We demonstrate that this signature, which we called iHet, is conserved in different cancers and associated with antitumor immunity. Through analysis of single-cell and spatial transcriptomics data, we trace back the cellular origin of the variability explaining the iHet signature. Finally, we demonstrate that iHet has predictive value for cancer immunotherapy, which can be further improved by disentangling three major determinants of anticancer immune responses: activity of immune cells, immune infiltration or exclusion, and cancer-cell foreignness. This work shows how transcriptomics data can be integrated to derive a holistic representation of the phenotypic heterogeneity of the TME and to predict its unfolding and fate during immunotherapy with immune checkpoint blockers.
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All authors

Lapuente-Santana, O.; Sturm, G.; Kant, J.; Ausserhofer, M.; Zackl, C.; Zopoglou, M.; McGranahan, N.; Rieder, D.; Trajanoski, Z.; Miranda, N.F.D.C. de; Eduati, F.; Finotello, F.

Date

2024-08-16

Journal

iScience

Volume

27

Issue

8

DOI

doi:10.1016/j.isci.2024.110529

Link

http://www.sciencedirect.com/science/article/pii/S2589004224017541?via%...