GATA-3 expression is not associated with complete pathological response in triple negative breast cancer patients treated with neoadjuvant chemotherapy

In Silico Analysis of Publicly Available Transcriptomic Data for the Identification of Triple-Negative Breast Cancer-Specific Biomarkers

BACKGROUND

Breast cancer is the most common type of cancer among women and is classified into multiple subtypes. Triple-negative breast cancer (TNBC) is the most aggressive subtype, with high mortality rates and limited treatment options such as chemotherapy and radiation. Due to the heterogeneity and complexity of TNBC, there is a lack of reliable biomarkers that can be used to aid in the early diagnosis and prognosis of TNBC in a non-invasive screening method.

AIM

This study aims to use in silico methods to identify potential biomarkers for TNBC screening and diagnosis, as well as potential therapeutic markers.

METHODS

Publicly available transcriptomic data of breast cancer patients published in the NCBI's GEO database were used in this analysis. Data were analyzed with the online tool GEO2R to identify differentially expressed genes (DEGs). Genes that were differentially expressed in more than 50% of the datasets were selected for further analysis. Metascape, Kaplan-Meier plotter, cBioPortal, and the online tool TIMER were used for functional pathway analysis to identify the biological role and functional pathways associated with these genes. Breast Cancer Gene-Expression Miner v4.7 was used to validify the obtained results in a larger cohort of datasets.

RESULTS

A total of 34 genes were identified as differentially expressed in more than half of the datasets. The DEG GATA3 had the highest degree of regulation, and it plays a role in regulating other genes. The estrogen-dependent pathway was the most enriched pathway, involving four crucial genes, including GATA3. The gene FOXA1 was consistently down-regulated in TNBC in all datasets.

CONCLUSIONS

The shortlisted 34 DEGs will aid clinicians in diagnosing TNBC more accurately as well as developing targeted therapies to improve patient prognosis. In vitro and in vivo studies are further recommended to validate the results of the current study.

Transcriptome Analysis Identifies GATA3-AS1 as a Long Noncoding RNA Associated with Resistance to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer Patients

Breast cancer is one of the leading causes of mortality in women worldwide, and neoadjuvant chemotherapy has emerged as an option for the management of locally advanced breast cancer. Extensive efforts have been made to identify new molecular markers to predict the response to neoadjuvant chemotherapy. Transcripts that do not encode proteins, termed long noncoding RNAs (lncRNAs), have been shown to display abnormal expression profiles in different types of cancer, but their role as biomarkers in response to neoadjuvant chemotherapy has not been extensively studied. Herein, lncRNA expression was profiled using RNA sequencing in biopsies from patients who subsequently showed either response or no response to treatment. The GATA3-AS1 transcript was overexpressed in the nonresponder group and was the most stable feature when performing selection in multiple random forest models. GATA3-AS1 was experimentally validated by RT-qPCR in an extended group of 68 patients. Expression analysis confirmed that GATA3-AS1 is overexpressed primarily in patients who were nonresponsive to neoadjuvant chemotherapy, with a sensitivity of 92.9%, a specificity of 75.0%, and an area under the curve of approximately 0.90, as measured by receiver operating characteristic curve analysis. The statistical model was based on luminal B-like patients and adjusted by menopausal status and phenotype (odds ratio, 37.49; 95% CI, 6.74-208.42; P = 0.001); GATA3-AS1 was established as an independent predictor of response. Thus, lncRNA GATA3-AS1 is proposed as a potential predictive biomarker of nonresponse to neoadjuvant chemotherapy.

Clinical Implications of Androgen-Positive Triple-Negative Breast Cancer

This review summarizes the recent findings of a vast array of studies conducted on androgen receptor-positive triple-negative breast cancer (AR-positive TNBC) to provide a better understanding of this specific breast cancer subgroup. AR expression is correlated with higher age, lower histological grade, lower proliferation index Ki-67, spiculated masses, and calcifications on mammography. Studies investigating the correlation between AR expression and lymph node metastasis are highly discordant. In addition, results regarding prognosis are highly contradictory. AR antagonists are a promising novel therapeutic approach in AR-positive TNBC. However, AR signaling pathways should be more investigated in order to understand the influence of AR expression on TNBC more thoroughly.

Predictive markers for pathological complete response after neo-adjuvant chemotherapy in triple-negative breast cancer

A combination of Sox10 and GATA3 was previously identified as a marker for metastatic triple-negative breast cancer (TNBC), but it is uncertain whether their expression is associated with pathological complete response (pCR) after neoadjuvant chemotherapy (NAC). This study investigates the predictive value of clinicopathological characteristics, as well as protein expression of Sox10, GATA3, p53 and p63, in a consecutive series of TNBC patients treated with NAC. Archived hematoxylin & eosin stained slides of core biopsies and resection specimens from 35 TNBC patients were reviewed. The following clinicopathological characteristics were determined at the biopsy level: age at diagnosis, cancer type, Nottingham grade, lympho-vascular invasion, syncytial growth, necrosis, clear cell differentiation, myxoid peritumor stroma, stromal tumor-infiltrating lymphocytes (sTILs) and presence of an in situ component. The MD Anderson residual cancer burden (RCB) score and corresponding RCB class were determined. Immunohistochemistry for Sox10, p53, GATA3 and p63 was performed at the biopsy level. sTILs, either as a continuous or as a dichotomous variable, were the only parameter that was significantly associated with pCR in univariable and multivariable analyses. Assessment of sTILs showed moderate to good interobserver agreement. High sTILs (≥40%) were significantly associated with increased pCR rates, and this association was observer-independent. This retrospective study of a consecutive community-based cohort of TNBC patients confirms that sTILs are a robust, observer-independent predictor for therapeutic response after NAC. The combination of Sox10, GATA3 and p53 immunoreactivity is unlikely to harbor any predictive value for pCR in TNBC.