A gene expression-based classifier for HER2-low breast cancer.

In clinical trials evaluating antibody-conjugated drugs (ADCs), HER2-low breast cancer is defined through protein immunohistochemistry scoring (IHC) 1+ or 2+ without gene amplification. However, in daily practice, the accuracy of IHC is compromised by inter-observer variability. Herein, we aimed to identify HER2-low breast cancer primary tumors by leveraging gene expression profiling. A discovery approach was applied to gene expression profile of institutional INT1 (n = 125) and INT2 (n = 84) datasets. We identified differentially expressed genes (DEGs) in each specific HER2 IHC category 0, 1+, 2+ and 3+. Principal Component Analysis was used to generate a HER2-low signature whose performance was evaluated in the independent INT3 (n = 95), and in the publicly available TCGA and GSE81538 datasets. The association between the HER2-low signature and HER2 IHC categories was evaluated by Kruskal-Wallis test with post hoc pair-wise comparisons. The HER2-low signature discriminatory capability was assessed by estimating the area under the receiver operating characteristic curve (AUC). Gene Ontology and KEGG analyses were performed to evaluate the HER2-low signature genes functional enrichment. A HER2-low signature was computed based on HER2 IHC category-specific DEGs. The twenty genes included in the signature were significantly enriched with lipid and steroid metabolism pathways, peptidase regulation, and humoral immune response. The HER2-low signature values showed a bell-shaped distribution across IHC categories (low values in 0 and 3+; high values in 1+ and 2+), effectively distinguishing HER2-low from 0 (p < 0.001) to 3+ (p < 0.001). Notably, the signature values were higher in tumors scored with 1+ as compared to 0. The HER2-low signature association with IHC categories and its bell-shaped distribution was confirmed in the independent INT3, TCGA and GSE81538 datasets. In the combined INT1 and INT3 datasets, the HER2-low signature achieved an AUC value of 0.74 (95% confidence interval, CI 0.67-0.81) in distinguishing HER2-low vs. the other categories, outperforming the individual ERBB2 mRNA AUC value of 0.52 (95% CI 0.43-0.60). These results represent a proof-of-concept for an observer-independent gene-expression-based classifier of HER2-low status. The herein identified 20-gene signature shows promise in distinguishing between HER2 0 and HER2-low expressing tumors, including those scored as 1+ at IHC, and in developing a selection approach for ADCs candidates.

Circulating miRNAs as Novel Non-Invasive Biomarkers to Aid the Early Diagnosis of Suspicious Breast Lesions for Which Biopsy Is Recommended.

In population-based screens, tissue biopsy remains the standard practice for women with imaging that suggests breast cancer. We examined circulating microRNAs as minimally invasive diagnostic biomarkers to discriminate malignant from benign breast lesions. miRNAs were analyzed by OpenArray in a retrospective cohort of plasma samples including 100 patients with malignant (T), 89 benign disease (B), and 99 healthy donors (HD) divided into training and testing sets and a prospective cohort (BABE) of 289 women with suspicious imaging findings who underwent tissue biopsy. miRNAs associated with disease status were identified by univariate analysis and then combined into signatures by multivariate logistic regression models. By combining 16 miRNAs differentially expressed in the T vs. HD comparison, 26 signatures were also able to significantly discriminate T from B disease. Seven of them, involving 5 specific miRNAs (miR-625, miR-423-5p, miR-370-3p, miR-181c, and miR-301b), were statistically validated in the testing set. Among the 7 signatures, the discriminatory performances of 5 were confirmed in the prospective BABE Cohort. This study identified 5 circulating miRNAs that, properly combined, distinguish malignant from benign breast disease in women with a high likelihood of malignancy.

A combination of extracellular matrix- and interferon-associated signatures identifies high-grade breast cancers with poor prognosis.

Breast cancer (BC) is a heterogeneous disease in which the tumor microenvironment (TME) seems to impact the clinical outcome. Here, we investigated whether a combination of gene expression signatures relating to both the structural and immune TME aspects can help predict prognosis in women with high-grade BC (HGBC). Thus, we focused on a combined molecular biomarker variable that involved extracellular matrix (ECM)-associated gene expression (ECM3 signature) and interferon (IFN)-associated metagene (IFN metagene) expression. In 97 chemo-naive HGBCs from the METABRIC dataset, the dichotomous ECM3/IFN (dECIF) variable identified a group of high-risk patients (ECM3+ /IFN- vs other; hazard ratio = 3.2, 95% confidence interval: 1.5-6.7). Notably, ECM3+ /IFN- tumors showed low tumor-infiltrating lymphocytes, high levels of CD33-positive cells, absence of PD-1 expression, or low expression of PD-L1, as suggested by immune profiles and immune-histochemical analysis on an independent cohort of 131 HGBCs. To make our results transferable to clinical use, we refined the dECIF biomarker using reduced ECM3 and IFN signatures; notably, the prognostic value of this reduced dECIF was comparable to that of the original dECIF. After validation in a new BC cohort, reduced dECIF was translated into a robust qPCR classifier for real-world clinical use.

Decoding Immune Heterogeneity of Triple Negative Breast Cancer and Its Association with Systemic Inflammation.

Triple negative breast cancer (TNBC) is an aggressive subtype with limited therapeutic options. New opportunities are emerging from current comprehensive characterization of tumor immune infiltration and fitness. Therefore, effectiveness of current chemotherapies and novel immunotherapies are partially dictated by host inflammatory and immune profiles. However, further progress in breast cancer immuno-oncology is required to reach a detailed awareness of the immune infiltrate landscape and to determine additional reliable and easily detectable biomarkers. In this study, by analyzing gene expression profiles of 54 TNBC cases we identified three TNBC clusters displaying unique immune features. Deep molecular characterization of immune cells cytolytic-activity and tumor-inflammation status reveled variability in the local composition of the immune infiltrate in the TNBC clusters, reconciled by tumor-infiltrating lymphocytes counts. Platelet-to-lymphocyte ratio (PLR), a blood systemic parameter of inflammation evaluated using pre-surgical blood test data, resulted negatively correlated with local tumoral cytolytic activity and T cell-inflamed microenvironment, whereas tumor aggressiveness score signature positively correlated with PLR values. These data highlighted that systemic inflammation parameters may represent reliable and informative markers of the local immune tumor microenvironment in TNBC patients and could be exploited to decipher tumor infiltrate properties and consequently to select the most appropriate therapies.

The PDGFRß/ERK1/2 pathway regulates CDCP1 expression in triple-negative breast cancer.

BACKGROUND: CDCP1, a transmembrane protein with tumor pro-metastatic activity, was recently identified as a prognostic marker in TNBC, the most aggressive breast cancer subtype still lacking an effective molecular targeted therapy. The mechanisms driving CDCP1 over-expression are not fully understood, although several stimuli derived from tumor microenvironment, such as factors present in Wound Healing Fluids (WHFs), reportedly increase CDCP1 levels. METHODS: The expression of CDCP1, PDGFRß and ERK1/2cell was tested by Western blot after stimulation of MDA-MB-231 cells with PDGF-BB and, similarly, in presence or not of ERK1/2 inhibitor in a panel of TNBC cell lines. Knock-down of PDGFRß was established in MDA-MB-231 cells to detect CDCP1 upon WHF treatment. Immunohistochemical staining was used to detect the expression of CDCP1 and PDGFRß in TNBC clinical samples. RESULTS: We discovered that PDGF-BB-mediated activation of PDGFRß increases CDCP1 protein expression through the downstream activation of ERK1/2. Inhibition of ERK1/2 activity reduced per se CDCP1 expression, evidence strengthening its role in CDCP1 expression regulation. Knock-down of PDGFRß in TNBC cells impaired CDCP1 increase induced by WHF treatment, highlighting the role if this receptor as a central player of the WHF-mediated CDCP1 induction. A significant association between CDCP1 and PDGFRß immunohistochemical staining was observed in TNBC specimens, independently of CDCP1 gene gain, thus corroborating the relevance of the PDGF-BB/PDGFRß axis in the modulation of CDCP1 expression. CONCLUSION: We have identified PDGF-BB/PDGFRß-mediated pathway as a novel player in the regulation of CDCP1 in TNCBs through ERK1/2 activation. Our results provide the basis for the potential use of PDGFRß and ERK1/2 inhibitors in targeting the aggressive features of CDCP1-positive TNBCs.

HER2 signaling enhances 5'UTR-mediated translation of c-Myc mRNA.

The increased levels of c-Myc protein observed previously in an ovarian carcinoma cell line stably transfected to express HER2 has suggested a role for the HER2 pathway in c-Myc expression. Analysis of HER2-transfected cells stimulated with heregulin beta1 (HRG) revealed increased c-Myc protein levels but not a corresponding increase in c-Myc mRNA expression or any change in c-Myc protein half-life. Transfection of HER2-overexpressing cells with a construct containing the 5' untranslated region (5'UTR) of c-Myc mRNA originated from the P2 promoter and placed upstream of the Renilla luciferase gene, enhanced reporter expression upon stimulation with HRG. The HRG-mediated increase in reporter activity correlated with the HRG-mediated induction observed for c-Myc protein, identifying the P2-derived leader (P2L) of c-Myc mRNA as the cis-element involved in c-Myc translational induction. Both the increase in c-Myc protein levels and P2L-enhanced translational activity were inhibited by the PI3K inhibitor wortmannin. Together, these results demonstrate that HRG stimulation of HER2 overexpressing cells leads to enhanced c-Myc protein synthesis through activation of the PI3K/Akt/mTOR pathway and that the P2L of c-Myc mRNA is the element responsible for induction of c-Myc translation.