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Identification and use of biomarkers in treatment strategies for triple-negative breast cancer subtypes.

ABSTRACT: Triple-negative breast cancer (TNBC) is a heterogeneous disease with distinct molecular subtypes that respond differentially to chemotherapy and targeted agents. The absence of high-frequency molecular alterations and a limited number of known biomarkers have limited the development of therapeutic strategies for the disease. Herein, we summarize the results of the first round of targeted therapy approaches in TNBC and discuss new preclinical strategies. Common themes emerge from the proposed strategies, such as the use of biomarkers to identify tumours with genomic instability, targeting adapted molecular states resulting from tumour suppressor loss, and targeting altered metabolic pathways.

SUBMITTER: Lehmann BD

PROVIDER: S-EPMC4090031 | biostudies-literature | 2014 Jan

REPOSITORIES: biostudies-literature

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Identification and use of biomarkers in treatment strategies for triple-negative breast cancer subtypes.

Lehmann Brian D BD Pietenpol Jennifer A JA

The Journal of pathology 20140101 2

Triple-negative breast cancer (TNBC) is a heterogeneous disease with distinct molecular subtypes that respond differentially to chemotherapy and targeted agents. The absence of high-frequency molecular alterations and a limited number of known biomarkers have limited the development of therapeutic strategies for the disease. Herein, we summarize the results of the first round of targeted therapy approaches in TNBC and discuss new preclinical strategies. Common themes emerge from the proposed str ...[more]

PMID: 24114677

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Project description:PurposeImmune checkpoint blockade (ICB) therapy has transformed the treatment of triple-negative breast cancer (TNBC) in recent years. However, some TNBC patients with high programmed death-ligand 1 (PD-L1) expression levels develop immune checkpoint resistance. Hence, there is an urgent need to characterize the immunosuppressive tumor microenvironment and identify biomarkers to construct prognostic models of patient survival outcomes in order to understand biological mechanisms operating within the tumor microenvironment.Patients and methodsRNA sequence (RNA-seq) data from 303 TNBC samples were analyzed using an unsupervised cluster analysis approach to reveal distinctive cellular gene expression patterns within the TNBC tumor microenvironment (TME). A panel of T cell exhaustion signatures, immunosuppressive cell subtypes and clinical features were correlated with the immunotherapeutic response, as assessed according to gene expression patterns. The test dataset was then used to confirm the occurrence of immune depletion status and prognostic features and to formulate clinical treatment recommendations. Concurrently, a reliable risk prediction model and clinical treatment strategy were proposed based on TME immunosuppressive signature differences between TNBC patients with good versus poor survival status and other clinical prognostic factors.ResultsSignificantly enriched TNBC microenvironment T cell depletion signatures were detected in the analyzed RNA-seq data. A high proportion of certain immunosuppressive cell subtypes, 9 inhibitory checkpoints and enhanced anti-inflammatory cytokine expression profiles were noted in 21.4% of TNBC patients that led to the designation of this group of immunosuppressed patients as the immune depletion class (IDC). Although IDC group TNBC samples contained tumor-infiltrating lymphocytes present at high densities, IDC patient prognosis was poor. Notably, PD-L1 expression was relatively elevated in IDC patients that indicated their cancers were resistant to ICB treatment. Based on these findings, a set of gene expression signatures predicting IDC group PD-L1 resistance was identified then used to develop risk models for use in predicting clinical therapeutic outcomes.ConclusionA novel TNBC immunosuppressive tumor microenvironment subtype associated with strong PD-L1 expression and possible resistance to ICB treatment was identified. This comprehensive gene expression pattern may provide fresh insights into drug resistance mechanisms for use in optimizing immunotherapeutic approaches for TNBC patients.

Dataset Information

Identification and use of biomarkers in treatment strategies for triple-negative breast cancer subtypes.

Publications

Identification and use of biomarkers in treatment strategies for triple-negative breast cancer subtypes.

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