| Literature DB >> 25774617 |
Carmen Criscitiello, Angela Esposito, Lucia Gelao, Luca Fumagalli, Marzia Locatelli, Ida Minchella, Laura Adamoli, Aron Goldhirsch, Giuseppe Curigliano.
Abstract
Immunotherapy for the treatment of breast cancer can be categorized as either (a) specific stimulation of the immune system by active immunization, with cancer vaccines, or (b) passive immunization, such as tumor-specific antibodies (including immune modulators) or adoptive cell therapy that inhibit the function of, or directly kill, tumor cells. We will present the current information and the future perspectives of immunotherapy in patients with breast cancer, including the prognostic role of tumor infiltrating lymphocytes, immune signatures, targeted therapies modulating the immune system, and tumor antigen cancer vaccines. Active immunotherapy in breast cancer and its implementation into clinical trials have been largely a frustrating experience in the last decades. The concept that the immune system regulates cancer development is experiencing a new era of interest. It is clear that the cancer immunosurveillance process indeed exists and potentially acts as an extrinsic tumor suppressor. Also, the immune system can facilitate tumor progression by sculpting the immunogenic phenotype of tumors as they develop. Cancer immunoediting represents a refinement of the cancer immunosurveillance hypothesis and resumes the complex interaction between tumor and immune system into three phases: elimination, equilibrium, and escape. Major topics in the field of immunology deserve a response: what do we know about tumor immunogenicity, and how might we therapeutically improve tumor immunogenicity? How can we modulate response of the immune system? Is there any gene signature predictive of response to immune modulators? The success of future immunotherapy strategies will depend on the identification of additional immunogenic antigens that can serve as the best tumor-rejection targets. Therapeutic success will depend on developing the best antigen delivery systems and on the elucidation of the entire network of immune signaling pathways that regulate immune responses in the tumor microenvironment.Entities:
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Year: 2014 PMID: 25774617 PMCID: PMC3978442 DOI: 10.1186/bcr3620
Source DB: PubMed Journal: Breast Cancer Res ISSN: 1465-5411 Impact factor: 6.466
Figure 1Immune system functions and components relevant to breast cancer therapy. CTLA-4, cytotoxic T lymphocyte-associated antigen 4; MHC, major histocompatibility complex; NK, natural killer; PD-1, programmed death-1; PDL-1, PD-1 ligand 1; TAA, tumor-associated antigen; TCR, T-cell receptor; Treg, regulatory T.
Immune signatures and their development
| Immune response (IR) module [ | A subclass of estrogen receptor-negative (ER−) tumors that overexpress IR genes and that have a good prognosis compared with the rest of ER− breast tumors independently of lymph node status or lymphocytic infiltration was identified. Subsequently, an associated module of complement and IR genes that define prognostic markers was identified and validated in over 240 ER− samples. |
| STAT1 module [ | On the basis of the literature, genes to act as ‘prototypes’ for different biological processes - ER for ER signaling, HER2 for HER2 signaling, AURKA for proliferation, CASP3 for apoptosis, VEGF for angiogenesis, PLAU for tumor invasion/metastasis, and, in this case, STAT1 for immune response - were selected. A comparison of linear models was then applied to generate modules of genes specifically associated with each of the prototype genes but not with the other prototypes. |
| B-cell metagene [ | Gene expression patterns of 200 patients who did not receive systemic treatment and co-regulated genes related to proliferation, steroid hormone receptor expression, and B-cell and T-cell infiltration were identified after hierarchical cluster analysis was performed. Metagenes were calculated as a surrogate for all genes contained within a particular cluster and their expression was correlated to time to metastasis. The B-cell metagene showed independent prognostic information in carcinoma with high proliferative activity. |
| IgG, HCK, MHC-I, MHC-II, LCK, STAT1, and IFN metagenes [ | Unsupervised hierarchical clustering of genes in 12 primary invasive breast cancer datasets as well as combined datasets revealed a large cluster of genes with functions in immune cells. Among this cluster, clusters that contained a minimum number of elements and a minimal average correlation were selected, and seven metagenes were derived. Each metagene then was associated with a cell type or immunological state or both. |
| HRneg/Tneg signature [ | A cohort of patients with node-negative, adjuvant treatment-naïve hormone receptor-negative (HRneg), and triple-negative (Tneg) breast cancer has been used to define and validate genes predictive for distant metastatic relapse. A composite HRneg/Tneg signature index was able to identify cases likely to remain free of metastatic relapse with high accuracy. Of note, significant positive correlation was observed between the HRneg/Tneg index and three independent immune-related signatures (STAT1, IFN, and IR), and network analysis showed that the signature was linked to immune/inflammatory cytokine regulation. |
| Support Vector Machine (SVM) classifier [ | Gene expression data of 2,145 invasive early breast adenocarcinomas were collected and used to test and validate the predictive performance of an SVM classifier based on a 368-gene expression signature associated with medullary breast carcinoma (MBC), which displays a basal profile but has good prognosis. The SVM model accurately classified all MBC samples in the learning and validation sets and was able to separate 466 cases of basal breast cancers into two subgroups (subgroup 1 and subgroup 2) containing, respectively, good- and poor-prognosis tumors. Ontology analysis revealed, among other features, effective IR in the good-prognosis subgroup. |
AURKA, aurora kinase A; CASP3, caspase 3; HCK, hemopoietic cell kinase; IFN, interferon; IgG, immunoglobulin G; LCK, lymphocyte-specific kinase; MHC, major histocompatibility complex; PLAU, Urokinase-type plasminogen activator; STAT1, signal transducer and activator of transcription 1; VEGF, vascular endothelial growth factor.