miRNAs and Long-term Breast Cancer Survival: Evidence from the WHEL Study

Evaluating the Role of Circulating MicroRNAs in Predicting Long-Term Survival Outcomes in Breast Cancer: A Prospective, Multicenter Clinical Trial

BACKGROUND

While long-term outcomes have improved for patients with breast cancer, 20% to 30% will still develop recurrence, and identifying these patients remains a challenge. MicroRNAs (miRNAs) are small, noncoding molecules that modulate genetic expression and affect oncogenesis.

STUDY DESIGN

This prospective, multicenter trial (ICORG10/11-NCT01722851) recruited patients undergoing neoadjuvant chemotherapy across 8 Irish centers. Predetermined miRNAs were quantified from patient whole blood using quantitative reverse transcriptase polymerase chain reaction. Venous sampling was performed at diagnosis (timepoint 1) and midway during neoadjuvant chemotherapy (timepoint 2 [T2]). miRNA expression profiles were correlated with recurrence-free survival (RFS), disease-free survival (DFS), and overall survival. Data analysis was performed using R v3.2.3.

RESULTS

A total of 124 patients were recruited with a median age of 55.0 years. The median follow-up was 103.1 months. Increased miR-145 expression at T2 was associated with improved RFS (hazard ratio 0.00; 95% confidence interval [CI] 0.00 to 0.99; p = 0.050). Using survival regression tree analysis, a relative cutoff of increased miR-145 expression greater than 0.222 was associated with improved RFS (p = 0.041). Increased miR-145 expression at T2 trended towards significance in predicting improved DFS (hazard ratio 0.00; 95% CI 0.00 to 1.42; p = 0.067). Using survival regression tree analysis, a relative cutoff of increased miR-145 expression greater than 0.222 was associated with improved DFS (p = 0.012). No miRNAs correlated with overall survival.

CONCLUSIONS

ICORG10/11 is the first Irish multicenter, translational research trial evaluating circulatory miRNAs as biomarkers predictive of long-term survival and correlated increased miR-145 expression with enhanced outcomes in early-stage breast cancer. Validation of these findings is required in the next generation of translational research trials.

MicroRNAs in Molecular Classification and Pathogenesis of Breast Tumors

The current clinical practice of breast tumor classification relies on the routine immunohistochemistry-based expression analysis of hormone receptors, which is inadequate in addressing breast tumor heterogeneity and drug resistance. MicroRNA expression profiling in tumor tissue and in the circulation is an efficient alternative to intrinsic molecular subtyping that enables precise molecular classification of breast tumor variants, the prediction of tumor progression, risk stratification and also identifies critical regulators of the tumor microenvironment. This review integrates data from protein, gene and miRNA expression studies to elaborate on a unique miRNA-based 10-subtype taxonomy, which we propose as the current gold standard to allow appropriate classification and separation of breast cancer into a targetable strategy for therapy.

MicroRNAs Patterns as Potential Tools for Diagnostic and Prognostic Follow-Up in Cancer Survivorship

Advances in screening methods and pharmacological treatments are increasing the life expectancy of cancer patients. During recent decades, the community of long-term disease-free cancer survivors (LCS) has grown exponentially, raising the issues related to cancer follow-up. Cancer relapse and other cancer-related diseases, as well as lifestyle, influence cancer survival. Recently, the regulatory role of microRNAs (miRNAs) in gene expression and their involvement in human diseases, including cancer, has been identified. Extracellular circulating miRNAs (ECmiRNAs) have been found in biological fluids and specific ECmiRNAs have been associated with cancer development and progression or with a therapy response. Here, we focus on the pivotal role of ECmiRNAs as biomarkers in cancer diagnosis and prognosis. Then, we discuss the relevance of ECmiRNAs expression in cancer survivors for the identification of specific ECmiRNAs profiles as potential tools to assess cancer outcome and to control LCS follow-up.

Individualized Prediction of Survival by a 10-Long Non-coding RNA-Based Prognostic Model for Patients With Breast Cancer

Deregulations of long non-coding RNAs (lncRNAs) have been implicated in the progression of breast cancer (BC). However, the prognostic values of those lncRNAs in BC remain elusive. This study aimed at constructing a lncRNA-based prognostic model to improve the clinical management of BC. Systematic investigation of lncRNA expression profiles and clinical data from The Cancer Genome Atlas (TCGA) database were utilized to establish a 10-lncRNA signature. The prognostic signature efficiently discriminated patients with significantly different prognosis regardless of intrinsic molecular subtypes and tumor-node-metastasis (TNM) stage. A combined model was constructed by multivariate Cox proportional hazards regression (CPHR) analysis, which combined the lncRNA-based signature with certain clinical risk factors (TNM stage, age, and human epidermal growth factor receptor 2 status). This model predicted a survival probability that closely corresponds to the actual survival probability. With respect to the entire set, the time-dependent receiver-operating characteristic curves revealed that the area under the curve of this model was the highest than any of the clinical risk factors. Moreover, functional enrichment analysis indicated that the molecular signature was mainly involved in DNA replication, which was firmly related to BC tumorigenesis. Consistent with the discovery, the knockdown of LHX1-DT, one of the 10 prognostic lncRNAs, attenuated the proliferation of BC cells in vitro and in vivo. Taken together, our study constructed a novel 10-lncRNA signature for prediction prognosis, and the signature-based model could provide new insight into accurate management of BC patients.

MiR-524-5p Suppresses Migration, Invasion, and EMT Progression in Breast Cancer Cells Through Targeting FSTL1

Background: The effects of miR-524-5p on breast cancer (BC) have not been investigated, though studies show that miR-524-5p has an anticancer function. Thus, this study investigated the effects of miR-524-5p on BC cells and its potential molecular mechanism. Materials and Methods: The expression of miR-524-5p from the collected BC samples was determined. Cell counting kit-8 (CCK-8) assay was performed to examine the effect of miR-524-5p on BC cells viability. The target for miR-524-5p was predicted by bioinformatics and further verified by luciferase assay. Wound healing assay and transwell assay were performed to determine cell migration and invasion of BC cells. The expressions of Follistatin-like 1 (FSTL1) and related proteins in epithelial-mesenchymal transition (EMT) were detected by Western blotting and quantitative real-time polymerase chain reaction. Results: MiR-524-5p was low-expressed in BC samples, and upregulation of miR-524-5p suppressed BC cell viability, migration, and invasion. FSTL1 was predicted as a target for miR-524-5p. In addition, overexpressed FSTL1 effectively abolished the effect of miR-524-5p on inhibiting FSTL1 expression, and reversed the inhibitory effects of miR-524-5p on the migration, invasion of BC cells as well as the effect of miR-524-5p on regulating the expressions of matrix metalloproteinase 2 (MMP2), matrix metalloproteinase 9 (MMP9), E-cadherin, and N-cadherin. Conclusions: Our findings suggest that miR-524-5p targeting FSTL1 adversely affects the progression of migration, invasion, and EMT of BC cells, thus, miR-524-5p is possibly a target for BC treatment.

Research-based PAM50 signature and long-term breast cancer survival

Purpose

Multi-gene signatures provide biological insight and risk stratification in breast cancer. Intrinsic molecular subtypes defined by mRNA expression of 50 genes (PAM50) are prognostic in hormone-receptor positive postmenopausal breast cancer. Yet, for 25–40% in the PAM50 intermediate risk group, long-term risk remains uncertain. Our study aimed to (i) test the long-term prognostic value of the PAM50 signature in pre- and post-menopausal breast cancer; (ii) investigate if the PAM50 model could be improved by addition of other mRNAs implicated in oncogenesis.

Methods

We used archived FFPE samples from 1723 breast cancer survivors; high quality reads were obtained on 1253 samples. Transcript expression was quantified using a custom codeset with probes for > 100 targets. Cox models assessed gene signatures for breast cancer relapse and survival.

Results

Over 15 + years of follow-up, PAM50 subtypes were (P < 0.01) associated with breast cancer outcomes after accounting for tumor stage, grade and age at diagnosis. Results did not differ by menopausal status at diagnosis. Women with Luminal B (versus Luminal A) subtype had a > 60% higher hazard. Addition of a 13-gene hypoxia signature improved prognostication with > 40% higher hazard in the highest vs lowest hypoxia tertiles.

Conclusions

PAM50 intrinsic subtypes were independently prognostic for long-term breast cancer survival, irrespective of menopausal status. Addition of hypoxia signatures improved risk prediction. If replicated, incorporating the 13-gene hypoxia signature into the existing PAM50 risk assessment tool, may refine risk stratification and further clarify treatment for breast cancer.

Electronic supplementary material

The online version of this article (10.1007/s10549-019-05446-y) contains supplementary material, which is available to authorized users.