Circulating microRNAs (miRNAs) are increasingly recognized as powerful biomarkers in several pathologies, including breast cancer. Here, their plasmatic levels were measured to be used as an alternative screening procedure to mammography for breast cancer diagnosis.A plasma miRNA profile was determined by RT-qPCR in a cohort of 378 women. A diagnostic model was designed based on the expression of 8 miRNAs measured first in a profiling cohort composed of 41 primary breast cancers and 45 controls, and further validated in diverse cohorts composed of 108 primary breast cancers, 88 controls, 35 breast cancers in remission, 31 metastatic breast cancers and 30 gynecologic tumors.A receiver operating characteristic curve derived from the 8-miRNA random forest based diagnostic tool exhibited an area under the curve of 0.81. The accuracy of the diagnostic tool remained unchanged considering age and tumor stage. The miRNA signature correctly identified patients with metastatic breast cancer. The use of the classification model on cohorts of patients with breast cancers in remission and with gynecologic cancers yielded prediction distributions similar to that of the control group.Using a multivariate supervised learning method and a set of 8 circulating miRNAs, we designed an accurate, minimally invasive screening tool for breast cancer.

Purpose: Here, we investigated the clinical relevance of an unprecedented combination of three biomarkers in triplenegative breast cancer (TNBC), both in human samples and in patient-derived xenografts of TNBC (PDX-TNBC): EGFR, its recently identified partner (MT4-MMP), and retinoblastoma protein (RB).Experimental Design: IHC analyses were conducted on human and PDX-TNBC samples to evaluate the production of the three biomarkers. The sensitivity of cancer cells expressing or not MT4-MMP to anti-EGFR (erlotinib) or anti-CDK4/6 inhibitor (palbociclib) was evaluated in vitro in 2D and 3D proliferation assays and in vivo using xenografts and PDX-TNBC displaying different RB, MT4-MMP, and EGFR status after single (erlotinib or palbociclib) or combined (erlotinib þ palbociclib) treatments.Results: EGFR and MT4-MMP were coexpressed in >70% of TNBC samples and PDX-TNBC, among which approximately 60% maintained RB expression. Notably, approximately 50% of all TNBC and PDX-TNBC expressed the three biomarkers. Single erlotinib and palbociclib treatments drastically reduced the in vitro proliferation of cells expressing EGFR and MT4-MMP when compared with control cells. Both TNBC xenografts and PDX expressing MT4-MMP, EGFR, and RB, but not PDX-TNBC with RB loss, were sensitive to erlotinib and palbociclib with an additive effect of combination therapy. Moreover, this combination was efficient in another PDX-TNBC expressing the three biomarkers and resistant to erlotinib alone.Conclusions: We defined a new association of three biomarkers (MT4-MMP/EGFR/RB) expressed together in 50% of TNBC and demonstrated its usefulness to predict the TNBC response to anti-EGFR and anti-CDK4/6 drugs used in single or combined therapy.

Non-coding RNAs (ncRNA) represent 1/5 of the mammalian transcript number, and 90% of the genome length is transcribed. Many ncRNAs play a role in cancer. Among them, non-coding natural antisense transcripts (ncNAT) are RNA sequences that are complementary and overlapping to those of either protein-coding (PCT) or non-coding transcripts. Several ncNATs were described as regulating protein coding gene expression on the same loci, and they are expected to act more frequently in cis compared to other ncRNAs that commonly function in trans. In this work, 22 breast cancers expressing estrogen receptors and their paired adjacent non-malignant tissues were analyzed by strand-specific RNA sequencing. To highlight ncNATs potentially playing a role in protein coding gene regulations that occur in breast cancer, three different data analysis methods were used: differential expression analysis of ncNATs between tumor and non-malignant tissues, differential correlation analysis of paired ncNAT/PCT between tumor and non-malignant tissues, and ncNAT/PCT read count ratio variation between tumor and non-malignant tissues. Each of these methods yielded lists of ncNAT/PCT pairs that were enriched in survival-associated genes. This work highlights ncNAT lists that display potential to affect the expression of protein-coding genes involved in breast cancer pathology.

Key Clinical MessageWe report a rare case of primary osteosarcoma of the breast in a patient who presented a calcified fibroadenoma one year before the appearance of the malignant lesion. We describe the follow‐up of the patient and the discovery of a similar osteosarcoma in the other breast one year later.

PurposeGenomic Grade Index (GGI) is a 97-gene signature that improves histologic grade (HG) classification in invasive breast carcinoma. In this prospective study we sought to evaluate the feasibility of performing GGI in routine clinical practice and its impact on treatment recommendations.MethodsPatients with pT1pT2 or operable pT3, N0-3 invasive breast carcinoma were recruited from 8 centers in Belgium. Fresh surgical samples were sent at room temperature in the MapQuant Dx™ PathKit for centralized genomic analysis. Genomic profiles were determined using Affymetrix U133 Plus 2.0 and GGI calculated using the MapQuant Dx® protocol, which defines tumors as low or high Genomic Grade (GG-1 and GG-3 respectively).Results180 pts were recruited and 155 were eligible. The MapQuant test was performed in 142 cases and GGI was obtained in 78% of cases (n=111). Reasons for failures were 15 samples with <30% of invasive tumor cells (11%), 15 with insufficient RNA quality (10%), and 1 failed hybridization (<1%). For tumors with an available representative sample (≥ 30% inv. tumor cells) (n=127), the success rate was 87.5%. GGI reclassified 69% of the 54 HG2 tumors as GG-1 (54%) or GG-3 (46%). Changes in treatment recommendations occurred mainly in the subset of HG2 tumors reclassified into GG-3, with increased use of chemotherapy in this subset.ConclusionThe use of GGI is feasible in routine clinical practice and impacts treatment decisions in early-stage breast cancer.Trial Registration ClinicalTrials.gov NCT01916837, http://clinicaltrials.gov/ct2/show/NCT01916837