Dataset Information

FOXA1 is Prognostic of Triple Negative Breast Cancers by Transcriptionally Suppressing SOD2 and IL6.

ABSTRACT: Having markers feasible for breast cancer subtyping, especially for triple negative breast cancer identification is crucial for improving the treatment outcome of such cancers. Here we explore the role of FOXA1 in characterizing triple negative breast cancers and the driving mechanisms. Through in vitro examination of the expression pattern at both transcriptional and translational levels, patient relapse-free survival analysis, immunohistochemistry staining and prediction power assessment using clinical samples, as well as functional studies, we systematically compared the role of FOXA1 in identifying triple negative and luminal type of breast cancers and explored the mechanisms driving such functionalities. We report that FOXA1 under-expression can lead to increased malignancy and cancer stemness, and is a subtyping marker identifying triple negative breast cancers rather than the luminal subtype by transcriptionally suppressing the expression of SOD2 and IL6. We are the first to systematically address the significance of FOXA1 in triple negative breast cancer identification as a biomarker and elucidate the mechanism at the molecular level, through a sequential bioinformatics analysis and experimental validations both in vitro and in clinics. Our discoveries compliment the current biomarker modalities once verified using larger clinical cohorts and improve the precision on characterizing breast cancer heterogeneity.

SUBMITTER: Dai X

PROVIDER: S-EPMC6535797 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

FOXA1 is Prognostic of Triple Negative Breast Cancers by Transcriptionally Suppressing SOD2 and IL6.

Dai Xiaofeng X Cheng Hongye H Chen Xiao X Li Ting T Zhang Jia J Jin Guoyin G Cai Dongyan D Huang Zhaohui Z

International journal of biological sciences 20190421 5

Having markers feasible for breast cancer subtyping, especially for triple negative breast cancer identification is crucial for improving the treatment outcome of such cancers. Here we explore the role of FOXA1 in characterizing triple negative breast cancers and the driving mechanisms. Through in vitro examination of the expression pattern at both transcriptional and translational levels, patient relapse-free survival analysis, immunohistochemistry staining and prediction power assessmen ...[more]

PMID: 31182923

Similar Datasets

Project description:BACKGROUND: A breast cancer prognostic tool should ideally be applicable to all types of invasive breast lesions. A number of studies have shown histopathological grade to be an independent prognostic factor in breast cancer, adding prognostic power to nodal stage and tumour size. The Nottingham Prognostic Index has been shown to accurately predict patient outcome in stratified groups with a follow-up period of 15 years after primary diagnosis of breast cancer. Clinically, breast tumours that lack the expression of Oestrogen Receptor, Progesterone Receptor and Human Epidermal growth factor Receptor 2 (HER2) are identified as presenting a "triple-negative" phenotype or as triple-negative breast cancers. These poor outcome tumours represent an easily recognisable prognostic group of breast cancer with aggressive behaviour that currently lack the benefit of available systemic therapy. There are conflicting results on the prevalence of lymph node metastasis at the time of diagnosis in triple-negative breast cancer patients but it is currently accepted that triple-negative breast cancer does not metastasize to axillary nodes and bones as frequently as the non-triple-negative carcinomas, favouring instead, a preferentially haematogenous spread. Hypothetically, this particular tumour dissemination pattern would impair the reliability of using Nottingham Prognostic Index as a tool for triple-negative breast cancer prognostication. METHODS: The present study tested the effectiveness of the Nottingham Prognostic Index in stratifying breast cancer patients of different subtypes with special emphasis in a triple-negative breast cancer patient subset versus non- triple-negative breast cancer. RESULTS: We demonstrated that besides the fact that TNBC disseminate to axillary lymph nodes as frequently as luminal or HER2 tumours, we also showed that TNBC are larger in size compared with other subtypes and almost all grade 3. Additionally, survival curves demonstrated that these prognostic factors are equally important to stratify different survival outcomes in non-TNBC as in TNBC. We also showed that the NPI retains the ability to stratify and predict survival of TNBC patients. CONCLUSION: The importance of this study relies on the need of prognostication improvements on TNBC, showing, at a clinical standpoint, that Nottingham Prognostic Index is as a truthful prognostic tool in TNBC.

Project description:BACKGROUND:Abundant evidence shows that triple-negative breast cancer (TNBC) is heterogeneous, and many efforts have been devoted to identifying TNBC subtypes on the basis of genomic profiling. However, few studies have explored the classification of TNBC specifically based on immune signatures that may facilitate the optimal stratification of TNBC patients responsive to immunotherapy. METHODS:Using four publicly available TNBC genomics datasets, we classified TNBC on the basis of the immunogenomic profiling of 29 immune signatures. Unsupervised and supervised machine learning methods were used to perform the classification. RESULTS:We identified three TNBC subtypes that we named Immunity High (Immunity_H), Immunity Medium (Immunity_M), and Immunity Low (Immunity_L) and demonstrated that this classification was reliable and predictable by analyzing multiple different datasets. Immunity_H was characterized by greater immune cell infiltration and anti-tumor immune activities, as well as better survival prognosis compared to the other subtypes. Besides the immune signatures, some cancer-associated pathways were hyperactivated in Immunity_H, including apoptosis, calcium signaling, MAPK signaling, PI3K-Akt signaling, and RAS signaling. In contrast, Immunity_L presented depressed immune signatures and increased activation of cell cycle, Hippo signaling, DNA replication, mismatch repair, cell adhesion molecule binding, spliceosome, adherens junction function, pyrimidine metabolism, glycosylphosphatidylinositol (GPI)-anchor biosynthesis, and RNA polymerase pathways. Furthermore, we identified a gene co-expression subnetwork centered around five transcription factor (TF) genes (CORO1A, STAT4, BCL11B, ZNF831, and EOMES) specifically significant in the Immunity_H subtype and a subnetwork centered around two TF genes (IRF8 and SPI1) characteristic of the Immunity_L subtype. CONCLUSIONS:The identification of TNBC subtypes based on immune signatures has potential clinical implications for TNBC treatment.

Dataset Information

FOXA1 is Prognostic of Triple Negative Breast Cancers by Transcriptionally Suppressing SOD2 and IL6.

Publications

FOXA1 is Prognostic of Triple Negative Breast Cancers by Transcriptionally Suppressing <i>SOD2</i> and <i>IL6</i>.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets