Spatial multiomics reveal intratumoral immune heterogeneity with distinct cytokine networks in lung cancer brain metastases
Christensson, Gustav LU
; Bocci, Matteo
LU
; Kazi, Julhash U
LU
; Durand, Geoffroy
LU
; Lanzing, Gustav
; Pietras, Kristian
LU
; Gonzalez Velozo, Hugo
and Hagerling, Catharina
LU
(2024)
In Cancer Research Communications
4(11).
p.2888-2902
- Abstract
The tumor microenvironment of brain metastases has become a focus in the development of immunotherapeutic drugs. However, countless brain metastasis patients have not experienced clinical benefit. Thus, understanding the immune cell composition within brain metastases, and how the immune cells interact with each other and other microenvironmental cell types, may be critical for optimizing immunotherapy. We applied spatial whole transcriptomic profiling with extensive multiregional sampling (19-30 regions per sample) and multiplex immunohistochemistry on formalin-fixed, paraffin-embedded lung cancer brain metastasis samples. We performed deconvolution of gene expression data to infer the abundances of immune cell populations and inferred... (More)
The tumor microenvironment of brain metastases has become a focus in the development of immunotherapeutic drugs. However, countless brain metastasis patients have not experienced clinical benefit. Thus, understanding the immune cell composition within brain metastases, and how the immune cells interact with each other and other microenvironmental cell types, may be critical for optimizing immunotherapy. We applied spatial whole transcriptomic profiling with extensive multiregional sampling (19-30 regions per sample) and multiplex immunohistochemistry on formalin-fixed, paraffin-embedded lung cancer brain metastasis samples. We performed deconvolution of gene expression data to infer the abundances of immune cell populations and inferred spatial relationships from the multiplex immunohistochemistry data. We also described cytokine networks between immune and tumor cells and used a protein language model to predict drug-target interactions. Finally, we performed deconvolution of bulk RNA data to assess the prognostic significance of immune-metastatic tumor cellular networks. We show that immune cell infiltration has a negative prognostic role in lung cancer brain metastases. Our in-depth multiomics analyses further reveal recurring intratumoral immune heterogeneity and the segregation of myeloid and lymphoid cells into distinct compartments that may be influenced by distinct cytokine networks. By employing computational modeling, we identify drugs that may target genes expressed in both tumor core and regions bordering immune infiltrates. Finally, we illustrate the potential negative prognostic role of our immune-metastatic tumor cellular networks. Our findings advocate for a paradigm shift from focusing on individual genes or cell types, towards targeting networks of immune and tumor cells.
(Less)
- author
- Christensson, Gustav
LU
; Bocci, Matteo
LU
; Kazi, Julhash U
LU
; Durand, Geoffroy
LU
; Lanzing, Gustav
; Pietras, Kristian
LU
; Gonzalez Velozo, Hugo
and Hagerling, Catharina
LU
- organization
- publishing date
- 2024-10-14
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Cancer Research Communications
- volume
- 4
- issue
- 11
- pages
- 2888 - 2902
- external identifiers
-
- scopus:85208687977
- pmid:39400127
- ISSN
- 2767-9764
- DOI
- 10.1158/2767-9764.CRC-24-0201
- language
- English
- LU publication?
- yes
- id
- 3fdab32d-2f64-4612-99ff-120e3aee6065
- date added to LUP
- 2024-10-16 19:22:17
- date last changed
- 2025-06-08 19:47:04
@article{3fdab32d-2f64-4612-99ff-120e3aee6065,
abstract = {{<p>The tumor microenvironment of brain metastases has become a focus in the development of immunotherapeutic drugs. However, countless brain metastasis patients have not experienced clinical benefit. Thus, understanding the immune cell composition within brain metastases, and how the immune cells interact with each other and other microenvironmental cell types, may be critical for optimizing immunotherapy. We applied spatial whole transcriptomic profiling with extensive multiregional sampling (19-30 regions per sample) and multiplex immunohistochemistry on formalin-fixed, paraffin-embedded lung cancer brain metastasis samples. We performed deconvolution of gene expression data to infer the abundances of immune cell populations and inferred spatial relationships from the multiplex immunohistochemistry data. We also described cytokine networks between immune and tumor cells and used a protein language model to predict drug-target interactions. Finally, we performed deconvolution of bulk RNA data to assess the prognostic significance of immune-metastatic tumor cellular networks. We show that immune cell infiltration has a negative prognostic role in lung cancer brain metastases. Our in-depth multiomics analyses further reveal recurring intratumoral immune heterogeneity and the segregation of myeloid and lymphoid cells into distinct compartments that may be influenced by distinct cytokine networks. By employing computational modeling, we identify drugs that may target genes expressed in both tumor core and regions bordering immune infiltrates. Finally, we illustrate the potential negative prognostic role of our immune-metastatic tumor cellular networks. Our findings advocate for a paradigm shift from focusing on individual genes or cell types, towards targeting networks of immune and tumor cells.</p>}},
author = {{Christensson, Gustav and Bocci, Matteo and Kazi, Julhash U and Durand, Geoffroy and Lanzing, Gustav and Pietras, Kristian and Gonzalez Velozo, Hugo and Hagerling, Catharina}},
issn = {{2767-9764}},
language = {{eng}},
month = {{10}},
number = {{11}},
pages = {{2888--2902}},
series = {{Cancer Research Communications}},
title = {{Spatial multiomics reveal intratumoral immune heterogeneity with distinct cytokine networks in lung cancer brain metastases}},
url = {{http://dx.doi.org/10.1158/2767-9764.CRC-24-0201}},
doi = {{10.1158/2767-9764.CRC-24-0201}},
volume = {{4}},
year = {{2024}},
}