Multi-omics profiling reveals distinct microenvironment characterization and suggests immune escape mechanisms of triple-negative breast cancer
Spotlight (1) Xiao Y (2) Ma D (3) Zhao S (4) Suo C (5) Shi J (6) Xue MZ (7) Ruan M (8) Wang H (9) Zhao J (10) Li Q (11) Wang P (12) Shi L (13) Yang WT (14) Huang W (15) Hu X (16) Yu K (17) Huang S (18) Bertucci F (19) Jiang YZ (20) Shao ZM
Xiao and Ma et al. used sequence information to define the tumor microenvironment of 386 triple-negative breast cancer patients and identified three tumor subsets. The first lacked immune infiltrate and cytokines and displayed MYC amplification. The second showed infiltration of non-activated innate immune cells, high levels of suppressive cytokines, and PI3K-AKT mutations. The third subset, which predicted better relapse-free and overall survival, displayed high innate and adaptive immune infiltration, cytokine levels, and expression of costimulatory checkpoint and antigen presentation molecules, which did not correlate with mutational burden.
Contributed by Alex Najibi
(1) Xiao Y (2) Ma D (3) Zhao S (4) Suo C (5) Shi J (6) Xue MZ (7) Ruan M (8) Wang H (9) Zhao J (10) Li Q (11) Wang P (12) Shi L (13) Yang WT (14) Huang W (15) Hu X (16) Yu K (17) Huang S (18) Bertucci F (19) Jiang YZ (20) Shao ZM
Xiao and Ma et al. used sequence information to define the tumor microenvironment of 386 triple-negative breast cancer patients and identified three tumor subsets. The first lacked immune infiltrate and cytokines and displayed MYC amplification. The second showed infiltration of non-activated innate immune cells, high levels of suppressive cytokines, and PI3K-AKT mutations. The third subset, which predicted better relapse-free and overall survival, displayed high innate and adaptive immune infiltration, cytokine levels, and expression of costimulatory checkpoint and antigen presentation molecules, which did not correlate with mutational burden.
Contributed by Alex Najibi
PURPOSE: The tumor microenvironment has a profound impact on prognosis and immunotherapy. However, the landscape of the triple-negative breast cancer (TNBC) microenvironment has not been fully understood. EXPERIMENTAL DESIGN: Using the largest original multi-omics dataset of TNBC (n = 386), we conducted an extensive immunogenomic analysis to explore the heterogeneity and prognostic significance of the TNBC microenvironment. We further analyzed the potential immune escape mechanisms of TNBC. RESULTS: The TNBC microenvironment phenotypes were classified into three heterogeneous clusters: cluster 1, the "immune-desert" cluster, with low microenvironment cell infiltration; cluster 2, the "innate immune-inactivated" cluster, with resting innate immune cells and nonimmune stromal cells infiltration; and cluster 3, the "immune-inflamed" cluster, with abundant adaptive and innate immune cells infiltration. The clustering result was validated internally with pathological sections and externally with TCGA and METABRIC cohorts. The microenvironment clusters had significant prognostic efficacy. In terms of potential immune escape mechanisms, cluster 1 was characterized by an incapability to attract immune cells, and MYC amplification was correlated with low immune infiltration. In cluster 2, chemotaxis but inactivation of innate immunity and low tumor antigen burden might contribute to immune escape, and mutations in the PI3K-AKT pathway might be correlated with this effect. Cluster 3 featured high expression of immune checkpoint molecules. CONCLUSIONS: Our study represents a step towards personalized immunotherapy for TNBC patients. Immune checkpoint inhibitors might be effective for "immune-inflamed" cluster, and the transformation of "cold tumors" into "hot tumors" should be considered for "immune-desert" and "innate immune-inactivated" clusters.
Author Info: (1) Department of Breast Surgery, Fudan University Shanghai Cancer Center. (2) Department of Breast Surgery, Fudan University Shanghai Cancer Center. (3) Department of Breast Surge
Author Info: (1) Department of Breast Surgery, Fudan University Shanghai Cancer Center. (2) Department of Breast Surgery, Fudan University Shanghai Cancer Center. (3) Department of Breast Surgery, Fudan University Shanghai Cancer Center. (4) Department of Epidemiology, School of Public Health, Fudan University. (5) Chinese National Human Genome Center and Shanghai Industrial Technology Institute (SITI). (6) SARI center for Stem Cell and Nanomedicine, Chinese Academy of Sciences. (7) Department of Pathology, Fudan University Shanghai Cancer Center. (8) Department of Breast Surgery, Fudan University Shanghai Cancer Center. (9) Fudan University Shanghai Cancer Center, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University. (10) Fudan University Shanghai Cancer Center and Institutes of Biomedical Sciences. (11) Bio-Med Big Data Center, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological sciences, Chinese Academy of Sciences. (12) Fudan University. (13) Department of Pathology, Fudan University Shanghai Cancer Center. (14) Department of Genetics, Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center and Shanghai Academy of Science and Technology. (15) breast surgery, Fudan Univeristy shanghai caner center. (16) Department of Breast Surgery, Fudan University. (17) Shanghai Cancer Center, Fudan University. (18) Medical Oncology, Institute Paoli-Calmettes. (19) Department of Breast Surgery, Fudan University Shanghai Cancer Center. (20) Breast Surgery, Fudan University Shanghai Cancer Center zhimin_shao@yeah.net.
Citation: Clin Cancer Res 2019 Mar 5 Epub03/05/2019