Transcript and protein signatures derived from shared molecular interactions across cancers are associated with mortality

Yelin Zhao; Xinxiu Li; Joseph Loscalzo; Martin Smelik; Oleg Sysoev; Yunzhang Wang; A K M Firoj Mahmud; Dina Mansour Aly; Mikael Benson

doi:10.1186/s12967-024-05268-7

Transcript and protein signatures derived from shared molecular interactions across cancers are associated with mortality

J Transl Med. 2024 May 11;22(1):444. doi: 10.1186/s12967-024-05268-7.

Authors

Affiliations

¹ Medical Digital Twin Research Group, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, Stockholm, Sweden.
² Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
³ Division of Statistics and Machine Learning, Department of Computer and Information Science, Linköping University, Linköping, Sweden.
⁴ Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden.
⁵ Medical Digital Twin Research Group, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, Stockholm, Sweden. mikael.benson@ki.se.

^# Contributed equally.

Abstract

Background: Characterization of shared cancer mechanisms have been proposed to improve therapy strategies and prognosis. Here, we aimed to identify shared cell-cell interactions (CCIs) within the tumor microenvironment across multiple solid cancers and assess their association with cancer mortality.

Methods: CCIs of each cancer were identified by NicheNet analysis of single-cell RNA sequencing data from breast, colon, liver, lung, and ovarian cancers. These CCIs were used to construct a shared multi-cellular tumor model (shared-MCTM) representing common CCIs across cancers. A gene signature was identified from the shared-MCTM and tested on the mRNA and protein level in two large independent cohorts: The Cancer Genome Atlas (TCGA, 9185 tumor samples and 727 controls across 22 cancers) and UK biobank (UKBB, 10,384 cancer patients and 5063 controls with proteomics data across 17 cancers). Cox proportional hazards models were used to evaluate the association of the signature with 10-year all-cause mortality, including sex-specific analysis.

Results: A shared-MCTM was derived from five individual cancers. A shared gene signature was extracted from this shared-MCTM and the most prominent regulatory cell type, matrix cancer-associated fibroblast (mCAF). The signature exhibited significant expression changes in multiple cancers compared to controls at both mRNA and protein levels in two independent cohorts. Importantly, it was significantly associated with mortality in cancer patients in both cohorts. The highest hazard ratios were observed for brain cancer in TCGA (HR [95%CI] = 6.90[4.64-10.25]) and ovarian cancer in UKBB (5.53[2.08-8.80]). Sex-specific analysis revealed distinct risks, with a higher mortality risk associated with the protein signature score in males (2.41[1.97-2.96]) compared to females (1.84[1.44-2.37]).

Conclusion: We identified a gene signature from a comprehensive shared-MCTM representing common CCIs across different cancers and revealed the regulatory role of mCAF in the tumor microenvironment. The pathogenic relevance of the gene signature was supported by differential expression and association with mortality on both mRNA and protein levels in two independent cohorts.

Keywords: Cancer-associated fibroblast; Cell–cell interactions; Mortality; Pan-cancer; Prioritization; Single-cell RNA sequencing.

Publication types

Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural

MeSH terms

Cell Communication
Cohort Studies
Female
Gene Expression Regulation, Neoplastic
Humans
Male
Middle Aged
Neoplasms* / genetics
Neoplasms* / mortality
RNA, Messenger / genetics
RNA, Messenger / metabolism
Transcriptome / genetics
Tumor Microenvironment / genetics

Substances

RNA, Messenger