Dataset Information

Extensive Transcriptomic and Genomic Analysis Provides New Insights about Luminal Breast Cancers.

ABSTRACT: Despite constituting approximately two thirds of all breast cancers, the luminal A and B tumours are poorly classified at both clinical and molecular levels. There are contradictory reports on the nature of these subtypes: some define them as intrinsic entities, others as a continuum. With the aim of addressing these uncertainties and identifying molecular signatures of patients at risk, we conducted a comprehensive transcriptomic and genomic analysis of 2,425 luminal breast cancer samples. Our results indicate that the separation between the molecular luminal A and B subtypes-per definition-is not associated with intrinsic characteristics evident in the differentiation between other subtypes. Moreover, t-SNE and MST-kNN clustering approaches based on 10,000 probes, associated with luminal tumour initiation and/or development, revealed the close connections between luminal A and B tumours, with no evidence of a clear boundary between them. Thus, we considered all luminal tumours as a single heterogeneous group for analysis purposes. We first stratified luminal tumours into two distinct groups by their HER2 gene cluster co-expression: HER2-amplified luminal and ordinary-luminal. The former group is associated with distinct transcriptomic and genomic profiles, and poor prognosis; it comprises approximately 8% of all luminal cases. For the remaining ordinary-luminal tumours we further identified the molecular signature correlated with disease outcomes, exhibiting an approximately continuous gene expression range from low to high risk. Thus, we employed four virtual quantiles to segregate the groups of patients. The clinico-pathological characteristics and ratios of genomic aberrations are concordant with the variations in gene expression profiles, hinting at a progressive staging. The comparison with the current separation into luminal A and B subtypes revealed a substantially improved survival stratification. Concluding, we suggest a review of the definition of luminal A and B subtypes. A proposition for a revisited delineation is provided in this study.

SUBMITTER: Tishchenko I

PROVIDER: S-EPMC4920434 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Extensive Transcriptomic and Genomic Analysis Provides New Insights about Luminal Breast Cancers.

Tishchenko Inna I Milioli Heloisa Helena HH Riveros Carlos C Moscato Pablo P

PloS one 20160624 6

Despite constituting approximately two thirds of all breast cancers, the luminal A and B tumours are poorly classified at both clinical and molecular levels. There are contradictory reports on the nature of these subtypes: some define them as intrinsic entities, others as a continuum. With the aim of addressing these uncertainties and identifying molecular signatures of patients at risk, we conducted a comprehensive transcriptomic and genomic analysis of 2,425 luminal breast cancer samples. Our ...[more]

PMID: 27341628

Similar Datasets

Project description:BACKGROUND:The ray floret shapes referred to as petal types on the chrysanthemum (Chrysanthemum × morifolium Ramat.) capitulum is extremely abundant, which is one of the most important ornamental traits of chrysanthemum. However, the regulatory mechanisms of different ray floret shapes are still unknown. C. vestitum is a major origin species of cultivated chrysanthemum and has flat, spoon, and tubular type of ray florets which are the three basic petal types of chrysanthemum. Therefore, it is an ideal model material for studying ray floret morphogenesis in chrysanthemum. Here, using morphological, gene expression and transcriptomic analyses of different ray floret types of C. vestitum, we explored the developmental processes and underlying regulatory networks of ray florets. RESULTS:The formation of the flat type was due to stagnation of its dorsal petal primordium, while the petal primordium of the tubular type had an intact ring shape. Morphological differences between the two ray floret types occurred during the initial stage with vigorous cell division. Analysis of genes related to flower development showed that CYCLOIDEA genes, including CYC2b, CYC2d, CYC2e, and CYC2f, were differentially expressed in different ray floret types, while the transcriptional levels of others, such as MADS-box genes, were not significantly different. Hormone-related genes, including SMALL AUXIN UPREGULATED RNA (SAUR), GRETCHEN HAGEN3 (GH3), GIBBERELLIN 2-BETA-DIOXYGENASE 1 (GA2OX1) and APETALA2/ETHYLENE RESPONSIVE FACTOR (AP2/ERF), were identified from 1532 differentially expressed genes (DEGs) in pairwise comparisons among the flat, spoon, and tubular types, with significantly higher expression in the tubular type than that in the flat type and potential involvement in the morphogenesis of different ray floret types. CONCLUSIONS:Our findings, together with the gene interactional relationships reported for Arabidopsis thaliana, suggest that hormone-related genes are highly expressed in the tubular type, promoting petal cell division and leading to the formation of a complete ring of the petal primordium. These results provide novel insights into the morphological variation of ray floret of chrysanthemum.

Project description:Integrating tumor heterogeneity in the drug discovery process is a key challenge to tackle breast cancer resistance. Identifying protein targets for functionally distinct tumor clones is particularly important to tailor therapy to the heterogeneous tumor subpopulations and achieve clonal theranostics. For this purpose, we performed an unsupervised, label-free, spatially resolved shotgun proteomics guided by MALDI mass spectrometry imaging (MSI) on 124 selected tumor clonal areas from early luminal breast cancers, tumor stroma, and breast cancer metastases. 2868 proteins were identified. The main protein classes found in the clonal proteome dataset were enzymes, cytoskeletal proteins, membrane-traffic, translational or scaffold proteins, or transporters. As a comparison, gene-specific transcriptional regulators, chromatin related proteins or transmembrane signal receptor were more abundant in the TCGA dataset. Moreover, 26 mutated proteins have been identified. Similarly, expanding the search to alternative proteins databases retrieved 126 alternative proteins in the clonal proteome dataset. Most of these alternative proteins were coded mainly from non-coding RNA. To fully understand the molecular information brought by our approach and its relevance to drug target discovery, the clonal proteomic dataset was further compared to the TCGA breast cancer database and two transcriptomic panels, BC360 (nanoString®) and CDx (Foundation One®). We retrieved 139 pathways in the clonal proteome dataset. Only 55% of these pathways were also present in the TCGA dataset, 68% in BC360 and 50% in CDx. Seven of these pathways have been suggested as candidate for drug targeting, 22 have been associated with breast cancer in experimental or clinical reports, the remaining 19 pathways have been understudied in breast cancer. Among the anticancer drugs, 35 drugs matched uniquely with the clonal proteome dataset, with only 7 of them already approved in breast cancer. The number of target and drug interactions with non-anticancer drugs (such as agents targeting the cardiovascular system, metabolism, the musculoskeletal or the nervous systems) was higher in the clonal proteome dataset (540 interactions) compared to TCGA (83 interactions), BC360 (419 interactions), or CDx (172 interactions). Many of the protein targets identified and drugs screened were clinically relevant to breast cancer and are in clinical trials. Thus, we described the non-redundant knowledge brought by this clone-tailored approach compared to TCGA or transcriptomic panels, the targetable proteins identified in the clonal proteome dataset, and the potential of this approach for drug discovery and repurposing through drug interactions with antineoplastic agents and non-anticancer drugs.

Dataset Information

Extensive Transcriptomic and Genomic Analysis Provides New Insights about Luminal Breast Cancers.

Publications

Extensive Transcriptomic and Genomic Analysis Provides New Insights about Luminal Breast Cancers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets