A signature of immune function genes associated with recurrence-free survival in breast cancer patients

Abstract

The clinical significance of tumor-infiltrating immune cells has been reported in a variety of human carcinomas including breast cancer. However, molecular signature of tumor-infiltrating immune cells and their prognostic value in breast cancer patients remain elusive. We hypothesized that a distinct network of immune function genes at the tumor site can predict a low risk versus high risk of distant relapse in breast cancer patients regardless of the status of ER, PR, or HER-2/neu in their tumors. We conducted retrospective studies in a diverse cohort of breast cancer patients with a 1–5 year tumor relapse versus those with up to 7 years relapse-free survival. The RNAs were extracted from the frozen tumor specimens at the time of diagnosis and subjected to microarray analysis and real-time RT-PCR. Paraffin-embedded tissues were also subjected to immunohistochemistry staining. We determined that a network of immune function genes involved in B cell development, interferon signaling associated with allograft rejection and autoimmune reaction, antigen presentation pathway, and cross talk between adaptive and innate immune responses were exclusively upregulated in patients with relapse-free survival. Among the 299 genes, five genes which included B cell response genes were found to predict with >85% accuracy relapse-free survival. Real-time RT-PCR confirmed the 5-gene prognostic signature that was distinct from an FDA-cleared 70-gene signature of MammaPrint panel and from the Oncotype DX recurrence score assay panel. These data suggest that neoadjuvant immunotherapy in patients with high risk of relapse may reduce tumor recurrence by inducing the immune function genes.

Beyond immune density: critical role of spatial heterogeneity in estrogen receptor-negative breast cancer

“…6 Methods to assess tumoral immune infiltration include traditional pathological examination and gene expression profiling. 7,8 Although the latter can indicate the immune cell type and their relative abundance, a more comprehensive analysis of their number, lineage and spatial distribution requires pathological assessment. [9][10][11][12] Spatial information on the tumor immune microenvironment is of clinical relevance, as not only the abundance and type but also the spatial locations of immune cells have been shown to be associated with clinical outcome in colorectal 13 and breast cancer.…”

Immunological metagene signatures derived from immunogenic cancer cell death associate with improved survival of patients with lung, breast or ovarian malignancies: A large-scale meta-analysis

“…50 The respective (Affymetrix) microarray gene expression data and clinical survival information from TCGA/caArray/GEO databases were analyzed through the KMPlotter platform 38,40,51 for breast cancer (n D 1115, derived from the following datasets: GSE1456, GSE16446, GSE20271, GSE20685, GSE20711, GSE3494 and GSE7390), ovarian cancer (n D 1436, derived from the following datasets: GSE14764, GSE15622, GSE18520, GSE19829, GSE23554, GSE26712, GSE30161, GSE3149, GSE9891, TCGA) and non-small cell lung cancer (n D 1432, derived from the following datasets: caArray, GSE14814, GSE19188, GSE29013, GSE31210, GSE3141, GSE37745, GSE4573, TCGA). These large datasets were considered as 'discovery datasets'.…”

Mapping spatial heterogeneity in the tumor microenvironment: a new era for digital pathology

“…18,29,30 Therefore, although a number of gene expression signatures have been published revealing high levels of molecular heterogeneity in immune infiltration, [31][32][33][34] pathological assessment remains critical for discerning tumor spatial heterogeneity. Lymphocytes can be identified based on their typical morphology of small, round and homogeneously basophilic nuclei which differentiates them from other leukocytes, such as neutrophils with more elongated and segmented nuclei.…”