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A combination of extracellular matrix- and interferon-associated signatures identifies high-grade breast cancers with poor prognosis.

ABSTRACT: Breast cancer (BC) is a heterogeneous disease in which the tumor microenvironment (TME) seems to impact the clinical outcome. Here, we investigated whether a combination of gene expression signatures relating to both the structural and immune TME aspects can help predict prognosis in women with high-grade BC (HGBC). Thus, we focused on a combined molecular biomarker variable that involved extracellular matrix (ECM)-associated gene expression (ECM3 signature) and interferon (IFN)-associated metagene (IFN metagene) expression. In 97 chemo-naive HGBCs from the METABRIC dataset, the dichotomous ECM3/IFN (dECIF) variable identified a group of high-risk patients (ECM3⁺ /IFN^- vs other; hazard ratio = 3.2, 95% confidence interval: 1.5-6.7). Notably, ECM3⁺ /IFN^- tumors showed low tumor-infiltrating lymphocytes, high levels of CD33-positive cells, absence of PD-1 expression, or low expression of PD-L1, as suggested by immune profiles and immune-histochemical analysis on an independent cohort of 131 HGBCs. To make our results transferable to clinical use, we refined the dECIF biomarker using reduced ECM3 and IFN signatures; notably, the prognostic value of this reduced dECIF was comparable to that of the original dECIF. After validation in a new BC cohort, reduced dECIF was translated into a robust qPCR classifier for real-world clinical use.

SUBMITTER: Lecchi M

PROVIDER: S-EPMC8096783 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

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A combination of extracellular matrix- and interferon-associated signatures identifies high-grade breast cancers with poor prognosis.

Lecchi Mara M Verderio Paolo P Cappelletti Vera V De Santis Francesca F Paolini Biagio B Monica Melissa M Sangaletti Sabina S Pupa Serenella Maria SM Iorio Marilena Valeria MV Bianchi Giulia G Gennaro Massimiliano M Fucà Giovanni G De Braud Filippo F Tagliabue Elda E Di Nicola Massimo M

Molecular oncology 20210219 5

Breast cancer (BC) is a heterogeneous disease in which the tumor microenvironment (TME) seems to impact the clinical outcome. Here, we investigated whether a combination of gene expression signatures relating to both the structural and immune TME aspects can help predict prognosis in women with high-grade BC (HGBC). Thus, we focused on a combined molecular biomarker variable that involved extracellular matrix (ECM)-associated gene expression (ECM3 signature) and interferon (IFN)-associated metag ...[more]

PMID: 33523584

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Project description:BackgroundRas suppressor 1 (RSU1), a highly conserved protein, plays an important role in actin cytoskeleton remodeling and cell-extracellular matrix adhesion. Aberration of RSU1 activity can cause changes in cell adhesion and migration, thereby enhancing tumor proliferation and metastasis. However, the correlation between RSU1 and gastrointestinal cancers (GICs), as well as its prognostic role related to tumor-infiltrating immune cells (TIICs) remains unclear.AimTo shows RSU1 plays a potential promoting role in facilitating tumor immune escape in GIC.MethodsDifferential expression of RSU1 in different tumors and their corresponding normal tissues was evaluated by exploring the Gene Expression Profiling Interactive Analysis (GEPIA) dataset. The correlation between RSU1 expression and prognosis of GIC cancer patients was evaluated by Kaplan-Meier plotter. Then, RSU1-correlated genes were screened and functionally characterized via enrichment analysis. The correlation between RSU1 and TIICs was further characterized using the Tumor Immune Estimation Resource (TIMER). In addition, the correlation between RSU1 and immune cell surface molecules was also analyzed by TIMER.ResultsHigh RSU1 expression was associated with poor overall survival of gastric cancer patients, exhibiting a hazard ratio (HR) = 1.36, first progression HR = 1.53, and post progression survival HR = 1.6. Specifically, high RSU1 Levels were associated with prognosis of gastric cancer in females, T4 and N3 stages, and Her-2-negative subtypes. Regarding immune-infiltrating cells, RSU1 expression level was positively correlated with infiltration of CD4+ T cells, macrophages, neutrophils, and dendritic cells (DCs) in colorectal adenocarcinoma and stomach adenocarcinoma. RSU1 expression was also predicted to be strongly correlated with immune marker sets in M2 macrophage, DCs and T cell exhaustion in GICs.ConclusionIn gastrointestinal cancers, RSU1 is increased in tumor tissues, and predicts poor survival of patients. Increased RSU1 may be involved in promoting macrophage polarization, DC infiltration, and T cell exhaustion, inducing tumor immune escape and the development of tumors in GICs. We suggest that RSU1 is a promising prognostic biomarker reflecting immune infiltration level of GICs, as well as a potential therapeutic target for precision treatment through improving the immune response.

Project description:BackgroundA major obstacle to the development of personalized therapies for gastric cancer (GC) is the prevalent heterogeneity at the intra-tumor, intra-patient, and inter-patient levels. Although the pathological stage and histological subtype diagnosis can approximately predict prognosis, GC heterogeneity is rarely considered. The extracellular matrix (ECM), a major component of the tumor microenvironment (TME), extensively interacts with tumor and immune cells, providing a possible proxy to investigate GC heterogeneity. However, ECM consists of numerous protein components, and there are no suitable models to screen ECM-related genes contributing to tumor growth and prognosis. We constructed patient-derived tumor xenograft (PDTX) models to obtain robust ECM-related transcriptomic signatures to improve GC prognosis prediction and therapy design.MethodsOne hundred twenty two primary GC tumor tissues were collected to construct PDTX models. The tumorigenesis rate and its relationship with GC prognosis were investigated. Transcriptome profiling was performed for PDTX-originating tumors, and least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to extract prognostic ECM signatures and establish PDTX tumorigenicity-related gene (PTG) scores. The predictive ability of the PTG score was validated using two independent cohorts. Finally, we combined PTG score, age, and pathological stage information to establish a robust nomogram for GC prognosis prediction.ResultsWe found that PDTX tumorigenicity indicated a poor prognosis in patients with GC, even at the same pathological stage. Transcriptome profiling of PDTX-originating GC tissues and corresponding normal controls identified 383 differentially expressed genes, with enrichment of ECM-related genes. A robust prognosis prediction model using the PTG score showed robust performance in two validation cohorts. A high PTG score was associated with elevated M2 polarized macrophage and cancer-associated fibroblast infiltration. Finally, combining the PTG score with age and TNM stage resulted in a more effective prognostic model than age or TNM stage alone.ConclusionsWe found that ECM-related signatures may contribute to PDTX tumorigenesis and indicate a poor prognosis in GC. A feasible survival prediction model was built based on the PTG score, which was associated with immune cell infiltration. Together with patient ages and pathological TNM stages, PTG score could be a new approach for GC prognosis prediction.

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A combination of extracellular matrix- and interferon-associated signatures identifies high-grade breast cancers with poor prognosis.

Publications

A combination of extracellular matrix- and interferon-associated signatures identifies high-grade breast cancers with poor prognosis.

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