Dataset Information

Clinical, pathological, and PAM50 gene expression features of HER2-low breast cancer.

ABSTRACT: Novel antibody-drug conjugates against HER2 are showing high activity in HER2-negative breast cancer (BC) with low HER2 expression (i.e., 1+ or 2+ and lack of ERBB2 amplification). However, the clinical and molecular features of HER2-low BC are yet to be elucidated. Here, we collected retrospective clinicopathological and PAM50 data from 3,689 patients with HER2-negative disease and made the following observations. First, the proportion of HER2-low was higher in HR-positive disease (65.4%) than triple-negative BC (TNBC, 36.6%). Second, within HR-positive disease, ERBB2 and luminal-related genes were more expressed in HER2-low than HER2 0. In contrast, no gene was found differentially expressed in TNBC according to HER2 expression. Third, within HER2-low, ERBB2 levels were higher in HR-positive disease than TNBC. Fourth, HER2-low was not associated with overall survival in HR-positive disease and TNBC. Finally, the reproducibility of HER2-low among pathologists was suboptimal. This study emphasizes the large biological heterogeneity of HER2-low BC, and the need to implement reproducible and sensitive assays to measure low HER2 expression.

SUBMITTER: Schettini F

PROVIDER: S-EPMC7782714 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Clinical, pathological, and PAM50 gene expression features of HER2-low breast cancer.

Schettini Francesco F Chic Nuria N Brasó-Maristany Fara F Paré Laia L Pascual Tomás T Conte Benedetta B Martínez-Sáez Olga O Adamo Barbara B Vidal Maria M Barnadas Esther E Fernández-Martinez Aranzazu A González-Farre Blanca B Sanfeliu Esther E Cejalvo Juan Miguel JM Perrone Giuseppe G Sabarese Giovanna G Zalfa Francesca F Peg Vicente V Fasani Roberta R Villagrasa Patricia P Gavilá Joaquín J Barrios Carlos H CH Lluch Ana A Martín Miguel M Locci Mariavittoria M De Placido Sabino S Prat Aleix A

NPJ breast cancer 20210104 1

Novel antibody-drug conjugates against HER2 are showing high activity in HER2-negative breast cancer (BC) with low HER2 expression (i.e., 1+ or 2+ and lack of ERBB2 amplification). However, the clinical and molecular features of HER2-low BC are yet to be elucidated. Here, we collected retrospective clinicopathological and PAM50 data from 3,689 patients with HER2-negative disease and made the following observations. First, the proportion of HER2-low was higher in HR-positive disease (65.4%) than ...[more]

PMID: 33397968

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Project description:Claudin-low breast cancer is a molecular type of breast cancer originally identified by gene expression profiling and reportedly associated with poor survival. Claudin-low tumors have been recognised to preferentially display a triple-negative phenotype, however only a minority of triple-negative breast cancers are claudin-low. We sought to identify an immunohistochemical profile for claudin-low tumors that could facilitate their identification in formalin fixed paraffin embedded tumor material. First, an in silico collection of ~1600 human breast cancer expression profiles was assembled and all claudin-low tumors identified. Second, genes differentially expressed between claudin-low tumors and all other molecular subtypes of breast cancer were identified. Third, a number of these top differentially expressed genes were tested using immunohistochemistry for expression in a diverse panel of breast cancer cell lines to determine their specificity for claudin-low tumors. Finally, the immunohistochemical panel found to be most characteristic of claudin-low tumors was examined in a cohort of 942 formalin fixed paraffin embedded human breast cancers with >10 years clinical follow-up to evaluate the clinico-pathologic and survival characteristics of this tumor subtype. Using this approach we determined that claudin-low breast cancer is typically negative for ER, PR, HER2, claudin 3, claudin 4, claudin 7 and E-cadherin. Claudin-low tumors identified with this immunohistochemical panel, were associated with young age of onset, higher tumor grade, larger tumor size, extensive lymphocytic infiltrate and a circumscribed tumor margin. Patients with claudin-low tumors had a worse overall survival when compared to patients with luminal A type breast cancer. Interestingly, claudin-low tumors were associated with a low local recurrence rate following breast conserving therapy. In conclusion, a limited panel of antibodies can facilitate the identification of claudin-low tumors. Furthermore, claudin-low tumors identified in this manner display similar clinical, pathologic and survival characteristics to claudin-low tumors identified from fresh frozen tumor material using gene expression profiling.

Project description:BackgroundTo investigate reliable associations between dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) features and gene expression characteristics in breast cancer (BC) and to develop and validate classifiers for predicting PAM50 subtypes and prognosis from DCE-MRI non-invasively.MethodsTwo radiogenomics cohorts with paired DCE-MRI and RNA-sequencing (RNA-seq) data were collected from local and public databases and divided into discovery (n = 174) and validation cohorts (n = 72). Six external datasets (n = 1,443) were used for prognostic validation. Spatial-temporal features of DCE-MRI were extracted, normalized properly, and associated with gene expression to identify the imaging features that can indicate subtypes and prognosis.ResultsExpression of genes including RBP4, MYBL2, and LINC00993 correlated significantly with DCE-MRI features (q-value < 0.05). Importantly, genes in the cell cycle pathway exhibited a significant association with imaging features (p-value < 0.001). With eight imaging-associated genes (CHEK1, TTK, CDC45, BUB1B, PLK1, E2F1, CDC20, and CDC25A), we developed a radiogenomics prognostic signature that can distinguish BC outcomes in multiple datasets well. High expression of the signature indicated a poor prognosis (p-values < 0.01). Based on DCE-MRI features, we established classifiers to predict BC clinical receptors, PAM50 subtypes, and prognostic gene sets. The imaging-based machine learning classifiers performed well in the independent dataset (areas under the receiver operating characteristic curve (AUCs) of 0.8361, 0.809, 0.7742, and 0.7277 for estrogen receptor (ER), human epidermal growth factor receptor 2 (HER2)-enriched, basal-like, and obtained radiogenomics signature). Furthermore, we developed a prognostic model directly using DCE-MRI features (p-value < 0.0001).ConclusionsOur results identified the DCE-MRI features that are robust and associated with the gene expression in BC and displayed the possibility of using the features to predict clinical receptors and PAM50 subtypes and to indicate BC prognosis.

Dataset Information

Clinical, pathological, and PAM50 gene expression features of HER2-low breast cancer.

Publications

Clinical, pathological, and PAM50 gene expression features of HER2-low breast cancer.

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