Abstract 170P
Background
Triple positive breast cancer (TPBC) overexpresses HER2 and enriches HR to estrogen and progesterone. Bidirectional cross-talk between HER2 pathways and estrogen receptor alpha (ERα) leads to tumor progression and resistance to targeted therapy for TPBC. To understand the molecular mechanisms of its antitumor response and identify ideal candidates for tailoring effective immunotherapy, we proposed a robust molecular classification of TPBC.
Methods
A training cohort of 85 TPBC and 91 healthy controls samples were obtained from TCGA and GTEx datebase with Clinical and biological data. After filtrating of differentially expressed genes (DEGs) between TPBC and HC, intersecting DEGs with immunity-related genes (IRGs), univariate cox analysis, non-negative matrix factorization (NMF), ssGSEA and annotating by using a set of immune-related gene signatures were applied to illustrate the immune landscapes of these patients for classification. The graph learning-based dimensionality reduction technique was applied to visualize the immune gene expression profiles. Tumor immune dysfunction and exclusion (TIDE) algorithm was performed to predict the likelihood of response to ICB immunotherapy of TPBC patients. Immune genomic classification was validated by 74 samples which obtained from GSE2109 and METABRIC database.
Results
Total 116 IRGs associated with prognosis were imported to NMF unsupervised machine learning method. Patients with TPBC were stratified into two subgroups based on a set of immune-related gene signatures. Approximately 45% of TPBCs in the cohort (38/85) named as Immune Class showed enriched inflammatory response and enhanced cytolytic activity, as well as better survival prognosis compared to the Non-Immune Class (P < 0.01). Immune Class showed potential response to immune checkpoint inhibitor (P < 0.01). The TIDE score of Immune Class was significantly lower compared with Non-Immune Class and may be responsible for resistance to ICB immunotherapy. (P < 0.001).
Conclusions
Immune subtype TPBC assumed to be more sensitive to immune checkpoint blockade therapy compared with Non-Immune Class TPBC. This novel classification may provide new insights for patients' selection of suitable immunotherapeutic treatments.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.