Methylome and transcriptome analyses reveal insights into the epigenetic basis for the good survival of hypomethylated ER-positive breast cancer subtype

Identification of UBFD1 as a prognostic biomarker and molecular target among estrogen receptor-positive breast cancer

Estrogen receptor (ER)-positive breast cancer (BRCA) is the most commonly diagnosed molecular subtype of BRCA. It is routinely treated with endocrine therapy; however, some patients relapse after therapy and develop drug resistance, resulting in treatment failure. In the present study, we identified markers of ER-positive BRCA and evaluated their putative function in immune infiltration as well as their clinicopathological significance. The ubiquitin family domain containing 1 (UBFD1) protein was associated with the prognosis of ER-positive BRCA patients. Its expression was higher in ER-positive BRCA tissues compared with adjacent nontumor tissues. Patients with higher UBFD1 expression had a poorer prognosis. UBFD1 is an independent risk factor for ER-positive BRCA patients and its function was primarily associated with hormone activity and inflammation. Taken together, UBFD1 is a potential prognostic biomarker and candidate target of ER-positive BRCA.

The regrouping of Luminal B (HER2 negative), a better discriminator of outcome and recurrence score

BACKGROUND

Breast cancer (BC) remains the leading cause of cancer-related deaths worldwide. High recurrence risk Luminal BC receives adjuvant chemotherapy in addition to standard hormone therapy. Considering the heterogeneity of Luminal B BC, a more accurate classification model is urgently needed.

METHODS

In this study, we retrospectively reviewed the data of 1603 patients who were diagnosed with HER2-negative breast invasive ductal carcinoma. According to the expression level of PR and Ki-67 index, the Luminal B (HER2-negative) BCs were divided into three groups: ER+PR-Ki67_low (ER-positive, PR-negative, and Ki-67 index <20%), ER+PR+Ki67_high (ER-positive, PR-positive, and Ki-67 index ≥20%), and ER+PR-Ki67_high (ER-positive, PR-negative, and Ki-67 index ≥20%). The cox proportional hazards regression model was used to evaluate the correlation between each variable and outcomes. Besides, discriminatory accuracy of the models was compared using the area under the receiver operating characteristic curve and log-rank χ² value.

RESULTS

The analysis results showed that there was a significant correlation between subtypes using this newly defined classification and overall survival (p < 0.001) and disease-free survival (DFS) (p < 0.001). Interestingly, patients in the ER+PR-Ki67_high subgroup have the worst survival outcome in Luminal B (HER2-negative) subtype, similar to Triple-negative patients. Besides, the ER+PR+Ki67_high has worse 5-year DFS compared with Luminal A group. There was a significant relationship between the regrouping subtype and the recurrence score index (RI) (p < 0.001). Moreover, the results showed that patients in ER+PR-Ki67_high subtype were more likely to have high RI for distance recurrence (RI-DR) and local recurrence (RI-LRR). Our newly defined classification has a better discrimination ability to predict survival outcome and recurrence score of Luminal B (HER2-negative) BC patients, which may help in clinical decision-making for individual treatment.

Development and Validation of a Prognostic Classifier Based on Lipid Metabolism-Related Genes for Breast Cancer

Background

The changes of lipid metabolism have been implicated in the development of many tumors, but its role in breast invasive carcinoma (BRCA) remains to be fully established. Here, we attempted to ascertain the prognostic value of lipid metabolism-related genes in BRCA.

Methods

We obtained RNA expression data and clinical information for BRCA and normal samples from public databases and downloaded a lipid metabolism-related gene set. Ingenuity Pathway Analysis (IPA) was applied to identify the potential pathways and functions of Differentially Expressed Genes (DEGs) related to lipid metabolism. Subsequently, univariate and multivariate Cox regression analyses were utilized to construct the prognostic gene signature. Functional enrichment analysis of prognostic genes was achieved by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Kaplan-Meier analysis, Receiver Operating Characteristic (ROC) curves, clinical follow-up results were employed to assess the prognostic potency. Potential compounds targeting prognostic genes were screened by Connectivity Map (CMap) database and a prognostic gene-drug interaction network was constructed using Comparative Toxicogenomics Database (CTD). Furthermore, we separately validated the selected marker genes in BRCA samples and human breast cancer cell lines (MCF-7, MDA-MB-231).

Results

IPA and functional enrichment analysis demonstrated that the 162 lipid metabolism-related DEGs we obtained were involved in many lipid metabolism and BRCA pathological signatures. The prognostic classifier we constructed comprising SDC1 and SORBS1 can serve as an independent prognostic marker for BRCA. CMap filtered 37 potential compounds against prognostic genes, of which 16 compounds could target both two prognostic genes were identified by CTD. The functions of the two prognostic genes in breast cancer cells were verified by cell function experiments.

Conclusion

Within this study, we identified a novel prognostic classifier based on two lipid metabolism-related genes: SDC1 and SORBS1. This result highlighted a new perspective on the metabolic exploration of BRCA.

Deciphering the nexus between the tumor immune microenvironment and DNA methylation in subgrouping estrogen receptor-positive breast cancer

BACKGROUND

Based on variable DNA methylation (DNAm), estrogen receptor (ER)-positive breast cancer (BRCA) is composed of two major subtypes, with the hypomethylated subgroup displaying good survival. Evidence indicates that the tumor microenvironment (TME) plays an important role in tumor progression and metastasis; however, its role and biological characteristics in DNAm-based subtypes of ER-positive BRCA remain largely unknown.

METHODS

Transcriptome data and matched clinical information of BRCA were downloaded from the Cancer Genome Atlas. Immune (ISs) and stromal scores (SSs) of BRCA patients were calculated using the ESTIMATE algorithm. Inferred fractions of 22 types of infiltrating immune cells of BRCA were collected from the Cancer Immunome Atlas.

RESULTS

The hypomethylated ER-positive BRCA subtype displayed high ISs, echoing the finding that higher ISs are associated with good BRCA survival. In addition, we analyzed the differentially expressed genes between the hypo-high-IS and hyper-low-IS BRCA subtypes in ER-positive patients and identified a co-expressed gene module (i.e., red module) enriched in immune-related biological processes (e.g., leukocyte activation involved in immune response). Moreover, four hub genes (i.e., PLEK, CD53, EVI2B, and CD4) in this module showed significant association between their expression and ER-positive BRCA survival.

CONCLUSIONS

We found differences in the tumor immune microenvironment (TIME) between DNAm-based BRCA subgroups in ER-positive patients and identified a specific module and hub genes involved to these differences. These findings elucidate the immunological basis for ER-positive BRCA progression and classification and provide potential gene biomarkers and targets for ER-positive BRCA diagnosis and treatment.